2nd International Conference on Computer, Cybernetics and Education (ICCCE-2024)

PROGRAMME OVERVIEW

Day 1 - 23rd February 2024

08:30 AM - 09:00 AM

Registration Desk

09:00 AM - 09:05AM

National anthem of Indonesia

09:05 AM - 09:10 AM

National Anthem of India

09:10 AM - 09:20 AM

Welcome speech by Moderator

09:20 AM - 09:30 AM

Welcome speech by Special Guest of Honor
@ Mr. A. Siddth Kumar Chhajer

Managing Director & Founder, Technoarete Groups, Chennai

09:30 AM - 10:00 AM

Speech by Keynote Speaker
Dr. Celestine Iwendi

Reader, School of Creative Technologies, The University of Bolton, United Kingdom

10:00 AM - 10:10 AM

Photographic Session

10:10 AM - 10:30 AM

Refreshment Break

10:30 AM - 11:30 AM

Technical Session 1 Session Speaker
Mr. Jose Manuel Perez Rebellon

Vice President, Enterprise Automation Director, City National Bank of Florida, United States of America

11:30 AM - 12:30 PM

Technical Session 2 Session Speaker
Dr. Anu Sayal


Senior Lecturer, Department of Mathematics/Statistics, Taylor’s University, Malaysia

12:30 PM - 01:30 PM

Lunch break

01:30 PM - 02:30 PM

Technical Session 3 Session Speaker
Dr. Vahab Iranmanesh


Programme Leader ( Master’s in cyber security), European Forensic Institute,United Kingdom

02:30 PM - 02:45 PM

Refreshment Break

02:45 PM - 02:55 PM

Valedictory

02:55 PM - 03:00 PM

Vote of Thanks

Day 2 - 24th February 2024

08:30 AM - 09:00 AM

Registration Desk

09:00 AM - 09:10 AM

Welcome Speech by Moderator

09:10 AM - 09:20 AM

National Anthem of India

09:10 AM - 09:20 AM

Welcome Speech by Conference Convener
Dr. Cecep E Rustana

Senior Lecturer,Department of Physics, Islamic State University of Maulana Malik Ibrahim, Indonesia.

09:20 AM - 09:50 AM

Speech by Keynote Speaker
Prof.Dr.Justin Paul

Director of Research, University of Puerto Rico, United States of America.

09:50 AM - 10:00 AM

Photographic Session

10:00 AM - 10:20 AM

Refreshment Break

10:20 AM - 11:20 AM

Technical Session 1 Session Speaker
Mr. Santosh Kamane

Co-Founder & CEO, CyberFIT Solutions Pvt Ltd, India.

11:20 AM - 12:20 PM

Technical Session 2 Session Speaker
Assoc. Prof. Dr. Hoshang Kolivand

Associate Professor, Faculty of Engineering and Technology, School of Computer Science and Mathematics, Liverpool John Moores University, United Kingdom

12:20 PM - 01:20 PM

Photographic Session

01:20 PM - 02:30 PM

Technical Session 3 Session Speaker
Prof. Dr. Paul Hollins


Professor, Cultural Research Development, School of Arts & Creative Technologies REF & KEF, The University of Bolton, United Kingdom

02:30 PM - 02:45 PM

Refreshment Break

02:45 PM - 02:55 PM

Valedictory

02:55 PM - 03:00 PM

Vote of Thanks

Keynote Speaker

Biography:

Celestine is an IEEE Brand Ambassador. He has a PhD in Electronics Engineering, ACM Distinguished Speaker, a Senior Member of IEEE, a Seasoned Lecturer and a Chartered Engineer. A highly motivated researcher and teacher with emphasis on communication, hands-on experience, willing-to-learn and a 23 years technical expertise. Celestine has been endorsed by the Royal Academy of Engineering under exceptional talent Scheme for his contribution to Artificial Intelligence and medical application. He has developed operational, maintenance, and testing procedures for electronic products, components, equipment, and systems; provided technical support and instruction to staff and customers regarding equipment standards, assisting with specific, difficult in-service engineering; Inspected electronic and communication equipment, instruments, products, and systems to ensure conformance to specifications, safety standards, and regulations. He is a wireless sensor network Chief Evangelist, AI, ML and IoT expert and designer. Celestine is a Reader (Professor) at the University of Bolton, United Kingdom. He is also the IEEE University of Bolton, Student Branch Counselor and former Board Member of IEEE Sweden Section, a Fellow of The Higher Education Academy, United Kingdom and a fellow of Institute of Management Consultants to add to his teaching, managerial and professional experiences. Visiting Professor to five Universities and an IEEE Humanitarian Philanthropist.

Dr. Celestine Iwendi

Reader

School of Creative Technologies
The University of Bolton
United Kingdom


Biography:

Dr Justin Paul, is the Chief Editor of Int Journal of Consumer studies, a top journal with an Impact Factor 10.0. Ranked among the top 92 highly cited Professors in Business & Economics subject areas, in the world, his citations are increasing at record rate 700 per month, with an H Index 69. He holds Ph.D in Business Administration from University of Brighton, England and another Ph.D from IIT. A former faculty member with the University of Washington, he is a Professor of MBA and Director-Research, University of Puerto Rico, USA and is an honorary Visiting Professor- University of Reading, England. He has also served as MBA Director & AACSB Co-ordinator at Nagoya University, Japan and as Department Chair at IIM. Dr. Paul introduced the Masstige model and measure for branding, CPP Model for internationalization, SCOPE framework for small firms, 7-P Framework for International Marketing, TCCM Framework and SPAR-4-SLR for literature reviews. He holds/held honorary 'Distinguished Vis Professor/Professor of Eminence' titles from - Lebanese American University, IIM, MS University, Parul University & SIBM. In addition, he has taught full courses in Denmark, France, Lithuania, Poland & serves/ed as keynote speaker at 100s of conferences incl UVSQ -France, KSMS-Korea, Polish academy & often in India. He was a visiting professor at University of Chicago, Vienna University of Eco and Bus- Austria, Fudan & UIBE-China, UAB- Barcelona and Madrid. He has published three best selling case studies with Ivey & Harvard. An author of books such as Business Environment, International Marketing, Services Marketing, Export-Import Management Management of Banking & Financial Services by McGraw-Hill, Oxford University Press & Pearson respectively. He is/was an Associate Editor with Journal of Business Research, European Management Review, & Euro Mgmt Journal. An author of over 180 articles in SSCI journals, he has over 75 papers are in A or A star journals of ABDC list. He has visited over 70 countries as a public speaker. He transformed IJCS as a journal with 2300 submissions in 2023 from 575 in 2019.

Prof.Dr.Justin Paul

Director of Research

University of Puerto Rico
United States of America


Scientific Session 3 Speaker

Biography:

Jose Manuel is a hands-on leader with over 20 years as Financial, Quality and AI Leader working primarily in the Financial Service industries. He received his BS from Javeriana University (Colombia) and his MBA from Wales University (UK), with different certification in IA from Oxford University, FIU, RPA Academy, Uipath, Nintex, AA also expert on six sigma and Agile methodology. Under his experience, he has created a successful CoE with more than 100 implemented bots, currently he is leading the CoE of the biggest bank in Florida, City National Bank of Florida, where the bank is transitioning from a traditional CoE (Center of Excellence RPA based) to a EoE (Ecosystem of Excellence) including CI, RPA, BPM, IDP, AI

Mr. Jose Manuel Perez Rebellon

Vice President

Enterprise Automation Director
City National Bank of Florida, United States of America


Scientific Session 5 Speaker

Biography:

Dr. Anu Sayal is currently working as Senior Lecturer in Mathematics/Statistics with Taylor’s University, Malaysia. She has done her schooling from Convent of Jesus and Mary, Dehradun. Her Post Graduation was in Mathematics from Guru Nanak Dev University, Amritsar. She has done her PhD in Mathematics from UTU Dehradun, India. She has won the “Young Scientist Award in Mathematics: Statistics and Computer Science from Uttarakhand Council for Science and Technology, Dehradun, Uttarakhand, India, during the 14th Uttarakhand State Science and Technology Congress 2019-20 held from 27th – 29th February 2020 at UCOST, Vigyan Dham, Dehradun, India. She has also received Teacher of the Year 2020 Award in September 2020 from Divya Himgiri in association with Uttarakhand Council for Science & Technology, Government of Uttarakhand, Commission for Scientific & Technical Terminology, MHRD, Govt. of India, New Delhi, India. She received Guruwarya samman 2021 award from Harvest educational transformational solutions (HETS). She also received the Best woman scientist award from Novel research academy in December 2021. She is also awarded as the Best teacher in January 2022 by Harvest educational transformational solutions. She has authored numerous research papers in reputed and prestigious journals (including Scopus & WOS), presented papers in many national and international conferences. She is serving as editorial board member and reviewer for various international journals (Scopus and WOS indexed). She has also attended various workshops and FDP’s. Her research interests include Fuzzy mathematics, Statistics, Numerical techniques, inventory and supply chain management.

Dr. Anu Sayal

Senior Lecturer

Department of Mathematics/Statistics
Taylor's University
Malaysia


Scientific Session 1 Speaker

Biography:

As a dedicated cybersecurity practitioner, Dr. Vahab Iranmanesh am driven by his passion for assisting organizations in enhancing their cybersecurity defenses. His diverse skill set encompasses expertise in governance, risk and compliance (GRC), comprehensive penetration testing for web applications and mobile applications (specifically Android), and safeguarding computer networks. Dr. Vahab possesses the skills and knowledge required to safeguard your sensitive data and systems effectively. His track record includes conducting numerous successful penetration tests for clients, during which he has identified vulnerabilities and provided actionable recommendations for remediation. With over a decade of hands-on experience in the field, Dr. Vahab has collaborated with clients across various industries to establish robust policies and procedures, thereby effectively mitigating cyber risks. His primary focus on governance, risk, and compliance ensures that your organization remains aligned with the latest industry standards and regulatory requirements. Beyond his practical experience, Dr. Vahab is also a dedicated cybersecurity lecturer and trainer. His commitment lies in sharing his wealth of knowledge with others. Dr. Vahab possesses the unique ability to simplify intricate technical concepts, making them easily understandable for professionals at all levels. As an educator, he is known for his effectiveness in imparting cybersecurity expertise to individuals seeking to strengthen their skills and knowledge in this ever-evolving field.

Dr. Vahab Iranmanesh

Programme Leader ( Master’s in cyber security)

European Forensic Institute
United Kingdom


Scientific Session 2 Speaker

Biography:

Hoshang Kolivand is an accomplished researcher in the field of computer science, specializing in AI and Mixed Reality. He received his MS degree in applied mathematics and computer from Amirkabir University of Technology, Iran, in 1999. He went on to pursue his PhD at the Media and Games Innovation Centre of Excellence (MaGIC-X) in Universiti Teknologi Malaysia, completing it in 2013. Dr. Kolivand further honed his expertise in Augmented Reality through a Post Doctoral program at UTM in 2014. With a rich academic background, Hoshang has previously served as a lecturer at Shahid Beheshti University, Iran, and later as a Senior Lecturer at Universiti Teknologi Malaysia. Currently, he holds the position of Reader(Associate Professor) in AI and Mixed Reality at Liverpool John Moores University and is also a Visiting Professor at Bharath Institute of Higher Education and Research: BIHER, Chennai, India. Throughout his career, Hoshang has made significant contributions to the academic community. He has authored numerous articles in international journals, conference proceedings, and technical papers, including book chapters. Additionally, he has published several books on object-oriented programming and mathematics. Dr. Kolivand is recognized as a Senior member of IEEE and actively contributes to various conferences and international journals as a Technical Program Committee (TCP) member. His dedication to advancing the field of computer science and his passion for research continue to drive his pursuit of knowledge and innovation.

Assoc. Prof. Dr. Hoshang Kolivand

Associate Professor

Faculty of Engineering and Technology
School of Computer Science and Mathematics
Liverpool John Moores University, United Kingdom


Scientific Session 4 Speaker

Biography:

Professor Paul Hollins is responsible for supporting collaborative research activities across the School of Arts. Paul is an experienced academic and has published extensively across a diverse range of subjects in the Arts, Education, Business and Technology domains.He is currently engaged by the university in the EU Horizon 2020 project RAGE (Realizing an Applied Gaming Ecosystem Europe), in chairing the Whitman 200 conference and in supporting the School of Arts collaborative research projects.

Prof. Dr. Paul Hollins

Professor, Cultural Research Development

School of Arts &Creative Technologies REF & KEF
The University of Bolton, United Kingdom


Scientific Session 4 Speaker

Biography:

As the Head of the Innovation Center of Excellence (CoE), He lead the development of AI products for Fortune 500 companies, leveraging my experience from my previous role as Chief Innovation Officer at TheLorry, a leading logistics provider in South East Asia. His expertise is rooted in a Ph.D. in Human-Computer Interaction, specializing in wearable devices, which complements my extensive background in product and software engineering, data science, and AI technologies. In his current role, he is responsible for strategizing AI product development, managing the creation of innovative solutions, and fostering a culture of excellence within the team. His leadership approach emphasizes nurturing talent, driving research in AI, and ensuring the highest standards of quality and compliance, making a key figure in shaping the future of AI innovation and development.

Dr. Waqas Khalid Obeidy

Head of Innovation (COE)

Mobiz
Malaysia


Technical Session

Paper Title:Students Performance Analysis

Abstract—

Using machine learning approaches, this work tackles the crucial problem of decreased student academic performance after COVID-19. The present research examines three learning algorithms, predicts student exam performance based on given information, and identifies factors impacting student achievement in order to find the most accurate algorithm for predicting exam results. Predicting exam success for students, choosing the best classifier (Logistic Regression, K-Nearest Neighbours, or Support Vector Machines) while minimizing overfitting and underfitting, and finding key performance indicators for early intervention are among the objectives. Categorical-to-numerical mapping and feature scaling were both a part of data preprocessing. Data visualization using Python modules helped to show trends and connections. In order to evaluate hyperparameter-tuned machine learning algorithms, accuracy, F1 score, ROC curves, and confusion matrices were used. In order to promote kids' educational journeys, educators, parents, and policymakers can benefit greatly from the identification of key success factors (parental education, study time, job ambitions) and hindrances (age, health, social involvement).

Keywords— Hyperparameter Tuning, Logistic Regression, SVM, KNN, Classifier Selection, Feature Scaling, Confusion Matrices

Bhairavi Pustode


Paper Title: A proposed framework of VAPT services in web application deployed on Infrastructure as a Service (IaaS)

Abstract—

Most companies in Malaysia require their employees to work from home due to the COVID-19 pandemic. This situation also increased the number of data generated from various sources, thus exposing them to different security risks. Even though the employees are encouraged to work from home because of the COVID-19 pandemic, they still need to communicate among themselves to do their work. However, working from home depends mainly on cloud computing (CC) applications that help employees accomplish their daily work efficiently. Injection attacks, such as SQL injection and Cross-Site Scripting (XSS), are critical security vulnerabilities that can lead to unauthorized access, data breaches, and potential service disruptions in web applications. With the increasing adoption of cloud computing, web applications deployed on cloud platforms like Amazon Web Services (AWS) are becoming more prevalent and vulnerable to such attacks. Therefore, it is crucial to develop practical Vulnerability Assessment and Penetration Testing (VAPT) techniques specifically tailored to identify and detect injection vulnerabilities in web applications deployed on AWS. However, existing VAPT methodologies often need more comprehensive coverage for injection vulnerabilities in cloud-based web applications, and they may not consider the unique characteristics and challenges associated with the AWS environment. This research addresses this gap by proposing an enhanced VAPT framework focusing specifically on injection attacks in web applications deployed on AWS.

Keyword: cloud computing, IaaS, Injection, SQL injection, Cross-Site Scripting (XSS), AWS and penetration testing.

Noraida Haji Ali


Paper Title: Unlocking the Potential of Hybrid Ensemble Techniques for Robust Botnet Detection: A Voting and Cascading Framework

Abstract—

Botnets, Enterprise-level infrastructures of jeopardized and breached computers, have manifested as a pivotal cybersecurity threat, posing ample risks to individuals, organizations, and core systems. Detecting botnets effectively remains a challenging task due to their dynamic nature, the competence to mimic legitimate traffic, and the perpetual evolution of onslaught methodologies. Ensemble learning techniques, combining assorted models, offer promising avenues for enhancing botnet detection accuracy. This paper explores the potential of hybrid ensemble techniques, incorporating voting and cascading strategies, for robust botnet detection. The study evaluates the performance of different voting and cascading schemes using the UNSW-NB15 dataset, a universally used benchmark for botnet detection. The results demonstrate that hybrid ensemble models employing voting and cascading strategies outperform individual models and conventional ensemble approaches. Moreover, the findings highlight the effectiveness of combining voting and cascading strategies, achieving superior detection accuracy while sustaining computational efficiency.

Keyword:Botnet detection, ensemble learning, voting, cascading, UNSW-NB15, hybrid models, machine learning, cybersecurity

Sharon R


Paper Title: Analysing Autism-Related Tweets through Twitter Dataset Visualization

Abstract—

In the dynamic landscape of social media, where intellectual discourse, information retrieval, and the exchange of ideas thrive, scholarly attention is increasingly drawn to the growing trend of users expressing viewpoints and ideas, notably manifested in a surge of daily tweets related to autism. This research explores the escalating phenomenon of users utilizing emojis, hashtags, reviews, and personal experiences on social media platforms to articulate their encounters with social challenges. The focal point of this research study is the development of the Autism Tweets Visualization Dashboard, a pivotal tool that categorizes and visually represents word usage across social media platforms. Beyond the identification of attitudes in user comments, this innovative dashboard serves as a real-time lens into contemporary social issues. The research aims to enhance public awareness of rights and security, offering valuable insights into a diverse array of perspectives and emotions. Utilizing sentiment analysis, the community gains the ability to swiftly showcase nationwide tweets, pinpointing content relevant to autism, and assessing public sentiment on specific subjects. This research contributes not only to understanding the dynamics of social media expression but also to empowering communities to engage in informed discussions, fostering a deeper understanding of the nuanced landscape of autism-related discourse in the digital realm.

Keyword: Autism Spectrum Disorder (ASD), media social, sentiment analysis

Norkhushaini Awang


Paper Title: Liver Tumour Detection using Machine Learning Algorithms

Abstract—

This paper presents a comprehensive study on liver tumour detection utilizing machine learning models, namely AlexNet, GoogLeNet, and RadioMix. To improve tumour detection accuracy, the suggested strategy uses an ensemble method that combines the advantages of these individual models. A wide range of datasets were used in numerous experiments to assess each model's and the ensemble's performance. The results demonstrate that the ensemble approach performs better than individual models and detects liver tumours with a higher degree of accuracy. By utilizing the distinct characteristics that each model extracts, the ensemble successfully mitigates the limitations that come with standalone architectures. This research contributes to the advancement of medical image analysis through the integration of machine learning models and ensemble strategies, presents a promising avenue for more accurate and reliable liver tumour detection. The results have important ramifications for enhancing clinical diagnostic performance.

Keyword: Liver Tumour detection, machine learning, ensemble, AlexNet, GoogLeNet, RadioMix

Shiny Fedora A


Paper Title: Collaborative Augmented Reality: A Proposed Technology Acceptance Model

Abstract—

A Collaborative Augmented Reality (CAR) system allows multiple users to communicate with each other in a shared 3D environment. While the Technology Acceptance Model (TAM) is a well-known method for predicting user acceptance of new technology, it also has the ability to utilize the two strongest dimensions of acceptance: perceived usefulness (PU) and perceived ease of use (PEOU). It can be further developed with external dimensions to investigate acceptance more comprehensively. Hence, the CAR system, with its 3D characteristics and collaborative ability, requires additional dimensions for measurement. This study aims to analyze and identify a suitable external dimension to be incorporated with TAM. We acquired the previous using the Web of Science database, which included keywords such as 'augmented reality,' 'virtual reality,' and 'technology acceptance model.' We analyzed eighteen high quality papers from a pool of ninety-seven papers, including journals and conferences. Resultantly, thirty-two external dimensions have been identified from previous TAM studies. After thorough analysis, a basic TAM for the CAR system is proposed, along with suggestions for external dimensions from different CAR domain applications. The TAM is expanded to include perceived enjoyment, aesthetic quality, system quality, social presence, satisfaction, information quality, interactivity, and embodiment quality in the CAR context. Other factors, such as social norms, mobility, and others, may be applicable to different CAR domain applications. The identified acceptance factors will assist researchers in enhancing their collaborative experience and conducting further analysis in the field of CAR.

Nur Asylah Suwadi


Paper Title:Revolutionizing Crypto Trading with Web3

Abstract—

A bank is a type of financial entity that offers loans to its stakeholders and accepts deposits. The branch of banking known as finance deals with settlement and controls cash withdrawal and deposit. Since the current era belongs to digital banking, where we can witness various security problems particularly in payment gateways, where hackers steal money from payment cards by sending the OTP to themselves, ewallets have evolved into a typical method of banking. The minimal amount is the starting point, but the impact grows as the per-transaction amount is raised with each attempt. This research paper examines how the banking sector may deal with transactional fraud effectively by ensuring authenticity through the use of a system powered by blockchain.

Zarinabegam k Mundargi


Paper Title:A Conceptual Architecture of Fuzzy Risk-Based Decision Support Systems (R+DSS)

Abstract—

This paper introduces a conceptual architecture for Fuzzy Risk-Based Decision Support Systems (R+DSS). This architecture is designed to provide a comprehensive and efficient approach to decision-making procedures in various domains involving assessing and controlling potential risks. The proposed architecture exhibits versatility in its applicability across multiple fields, such as finance, healthcare, engineering, and environmental management. It incorporates these components flexibly and scalable while also being user-friendly. The framework employs fuzzy logic principles such as membership functions, rule sets, and inference methods to facilitate a thorough evaluation of the risk that accommodates the inherent uncertainties and imprecisions characteristic of real-world risk scenarios. The Fuzzy Inference Engine is a versatile and resilient risk analysis tool capable of accommodating diverse data and systems, enabling effective risk mitigation strategies. The adaptability of this architecture to effectively handle complex, uncertain and dynamic environments makes it a promising tool for decision-makers looking to improve risk assessment and management protocols.

Keyword: Risk-Based, Decision Support Systems, Architecture, R+DSS.

Mohamad Jazli Shafizan Jaafar


Paper Title:Innovative Strategies for Blended Learning

Abstract—

Nowadays language classrooms are embraced with different forms of technology including digital learning tools, which increase student’s engagement and motivation and accelerates learning beyond the walls of a classroom. This presentation aims to introduce the impact of digital affordances by implementing different digital language learning tools like Padlet, Quizlet and Edpuzzle in college classrooms, which can substantially promote collaborative and responsive learning. A key point in using any of the tools depends on the level of users and type of activity. A study was conducted to determine whether these language tools are effective for student’s achievement in language classrooms in an English as Foreign Language (EFL) setting. Data was gathered from 100 students participating in this study through a questionnaire. Assessment results and attendance records of the students were also examined to support the research findings. It was observed that these learning apps help the students become more autonomous and responsible learners in language learning. The results also showed that technology is a significant factor in enhancing student’s academic achievement. The study provides remarkable insights for the effectiveness of blended learning incorporating instructional technology.

Yevette Mathew


Paper Title:Security and Privacy Preserving Solution for Blockchain: Reviews and Challenges

Abstract—

A block of transactions is a collection of recorded transactions. Each block is linked together using cryptography and includes transaction data, a timestamp, and a cryptographic hash of the block before it. This is based on distributed ledger technology and can be used with a variety of Internet-based interactive systems, including the Internet of Things, Identity Management, and Supply Chain Management. However, some privacy issues make it difficult to use in practise. This study aims to explore current security risks and privacy concerns related to the blockchain. We have talked about the present privacy-preserving cryptographic defence methods as well as the advantages and disadvantages of the cryptographic defence mechanisms utilised in the current real-world applications

Keyword: blockchain, cryptography, cryptocurrency, privacy.

R. Rajakarthik


Paper Title:Learning Through Kahoot

Abstract—

The wide range of modern technologies made the learning process easy for students and teachers. Students today are more motivated and engaged inside the classroom as they have various ways of learning. Kahoot is one of the best technologies that can be utilized in the classroom environment to serve both students and their teachers. This unique application is an innovative educational platform that revolutionizes traditional learning methods through gamification. This abstract explores Kahoot's impact on education, emphasizing its interactive nature, engagement strategies, and effectiveness in fostering collaborative learning environments. It examines Kahoot's versatile applications across diverse subjects and age groups, highlighting its ability to captivate learners' attention and enhance knowledge retention. Additionally, it discusses the platform's user-friendly interface, accessibility, and adaptability to various educational settings, making it a valuable tool for educators worldwide. This abstract underscores Kahoot's significance in promoting active participation, knowledge acquisition, and overall academic engagement among students, ultimately contributing to a more dynamic and enjoyable learning experience.

Tahani Al Nadabi


Paper Title:The Essence of Benchmarking in Assessments

Abstract—

Instructors use various assessment methods to analyze the understanding level of the students in each course. The evaluation elements may vary in terms of the criteria depending on each course. These methods are successful depending on various criteria depending on the needs of the course. The collective feedback of these assessments is measurable and valid through benchmarking with other institutions. There are numerous ways to make our assessments approachable and applicable, but those never determine the needs of the students. Assessment is a maze where students attempt different assessments like diagnostics, summative, and formative. Also, the main hold remains on the instructor to collaborate on the tasks efficiently and initiate the students to bring out the required skills like critical thinking, problem-solving, communication, and creativity along with their knowledge on the subject. The assessment succeeds only when it accomplishes the principles of assessment. Henceforth, the tests succeed in these components of validity, fairness, consistency, reliability, and authenticity by using a proper channel of benchmarking. Benchmarking helps instructors to receive proper feedback and support to move forward for further improvements and challenging changes. I shall show light on various types of benchmarking and the real essence of implementing them.

Ms Runitha Lourdes


Paper Title:Solving the Medical Device Supplier Selection Problem using Integrated AHP-TOPSIS Method: A Case of Sample Hospital in Thailand

Abstract—

Recently, the outbreak of the COVID-19 has made the medical device industry become one of the most prominent industries which is greatly developed by the Thai government. At the same time, for hospitals and related medical institutions, the selection of medical device suppliers has become a crucial issue that cannot be ignored. The research objective of this article is to apply analytic hierarchy process (AHP) integrated with technique for order preference by similarity to ideal solution (TOPSIS) to help a Thai hospital select a suitable medical device supplier from four suppliers. The main criteria considered during the supplier selection this time include: price, payment, delivery time, service, setting up a budge, and quality. Using the AHP method, first identify criteria service as the main element to consider among the six key criteria, followed by criteria quality. Through the TOPSIS method and sorting the final calculated relative closeness, it can be analyzed that supplier A2 is the most suitable alternative, followed by supplier A1. The results of this survey once again confirm that the comprehensive application of AHP-TOPSIS can effectively solve the multi criteria decision-making problem like selecting medical device suppliers, providing a reference and feasible solution template for such problems.

Keyword:Medical Device Supplier Selection, AHP, TOPSIS

Juan DING


Paper Title:Solving the Medical Device Supplier Selection Problem using Integrated AHP-TOPSIS Method: A Case of Sample Hospital in Thailand

Abstract—

Facing the long-term market demand caused by Thailand's aging population and the outbreak of the COVID-19, while setting up hospitals and medical institutions to maintain people's demand for medical treatment, the utilization rate of various medical devices has also increased sharply, inevitably resulting in an urgent problem, namely, the maintenance of medical devices. The goal of this paper is to combine two decision-making mathematical models, AHP (Analytic Hierarchy Process) and TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), to solve the site selection problem for a medical device maintenance center in western Thailand. This case comprehensively considers and analyzes ten key factors that affect the site selection with four candidate locations. After conducting interviews and research with seven senior experts from the medical device maintenance industry, and combining AHP and TOPSIS calculations, two main data analysis results were obtained. The weight values of the ten key factors obtained from the AHP operation indicate the three most important influencing factors, first customer quantity, second opportunities for the future, then making a profit. Based on another set of values of relative closeness calculated by TOPSIS, it can be concluded that position Prachuap Khiri Khan is the optimal solution for the case. The AHP-TOPSIS model proposed in this article fully utilizes the advantages of both algorithms and simplifies the calculation process to a certain extent. This model can be applied to address similar issues in medical industries, and can even be utilized in a wider range of multi criteria decision-making issues.

Keyword:AHP, TOPSIS, MCDM, Medical Device Maintenance Industry.

Daidi XIE


Paper Title:Improving the predictive validity of Situational Judgement Test within the Engineering Management discipline

Abstract—

Situational Judgment Tests (SJTs) have gained considerable popularity in assessing job-related competencies and predicting future job performance across various industries. Nevertheless, in spite of their widespread usage, there persists a consistent challenge in augmenting the prognostic validity of SJTs to accurately anticipate an individual's triumph in a given position. The extant issue revolves around the disparity between SJT scores and tangible on-the-job performance outcomes. While SJTs provide a promising instrument for evaluating an individual's behaviors and decision-making in work-related scenarios, the association between test performance and subsequent job performance necessitates refinement. This incongruity engenders concerns regarding the efficacy of SJTs in effectively identifying and selecting candidates who will excel in their respective roles, giving rise to potential incongruences between the chosen candidates and the job prerequisites. This investigation aims to undertake a comprehensive appraisal and examination of strategies to enhance the prognostic validity of SJTs in the assessment of job performance. It will delve into various methodologies, modifications, and advancements within SJT frameworks to address the identified underlying causes and ameliorate their effectiveness in prognosticating job success.

Ronen MOLLIK


Paper Title:Design Development Of Arabic-Rumi Transliteration Module With Virtual Reality Concept (eTARRiM) To Improve Primary School Students' Arabic Reading Skills : Needs Analysis

Abstract—

This study discusses the development of the Arabic-Romani Transliteration Module with a Virtual Reality Concept (eTARRiM) as an innovation in improving Arabic reading skills among primary school students. Needs analysis is done to solve the main issues in learning Arabic and develop a module that can overcome these challenges. A comprehensive literature review on Arabic language learning approaches, the concept of Arabic-Romani transliteration, and the application of reality technology may form the basis of the development of this module. With the importance of reading skills, this study gives special emphasis to Malay speaking students who face challenges in understanding the structure of Arabic writing. The eTARRiM module is designed to meet the needs of students by integrating Arabic-Romani transliteration as a bridge to understanding Arabic characters. Virtual reality technology is used to create an engaging and interactive learning environment. The needs analysis also follows the module elements such as the concept of transliteration, the use of technology, and how this module supports the needs of students in primary school. By understanding the critical issues in learning Arabic, this study offers a holistic view of relevant and effective development modules. The results of the study are expected to contribute to the development of more dynamic Arabic language learning resources, especially at the primary school level. Practical implications and recommendations for future research are also discussed to improve the quality of teaching and learning Arabic among primary school students.

Norazman Bin Ahmat Syafri


Paper Title:Study on Pozzolanic Behavior of Bamboo Fibre Reinforced Mortar with Bottom Ash as a Complementary Binder

Abstract—

The use of alternative building materials can contribute to reduction in cost and environmental hazard associated with cement production as well as waste pollution caused by the bottom ash. Bamboo is one of the sustainable materials which are in practice in the construction industry since many years. This paper concentrates on the efficient use of bamboo fibre (BF) and bottom ash (BA) to create an alternative building material. In order to improve the mechanical properties of the system, alkali treated BF with is used as an additive (0.5% to 2.5%) and BA is utilized to replace cement constantly at 10% for all the trial mixes. Sodium carboxymethyl cellulose (CMC) is used as dispersing agent at 1% for all the trial mixes. Fine aggregate is totally replaced by copper slag (CS) for all the trial mixes. Compressive strength test, water absorption test and dry density test were performed on the cube specimens and the flexural strength test was performed on the prism specimens. Comparative study was done on the bamboo fibre reinforced mortar specimens over the conventional mortar specimens. The effective proportions of the mortar indicate that using bottom ash and adding bamboo fibre may be a long-term option for a brighter tomorrow.

Keyword:Sustainable Materials; Bottom Ash; Bamboo Fibre; Copper Slag; Sodium Carboxymethyl Cellulose

Prem Kumar V


Paper Title:Systematic review and meta-analysis of the effect of the flipped teaching model on students' physical education learning

Abstract—

Flipped teaching method is a new teaching method, which reverses the time inside and outside the classroom, so that students can watch the teacher's video before or after class and learn knowledge independently through the network platform, while the knowledge is internalized and applied through interaction, cooperation, exploration and other ways in the classroom. In recent years, this teaching method has been paid more and more attention and applied in physical education. This paper aims to explore the effect of flipped teaching method on students' physical education learning through systematic review and Meta-analysis. We searched PubMed, web of science, Google Scholar, EBSCO, and Scopus databases for studies on the application of flipped teaching method in physical education from 2018 to 2023. A total of 8 studies that met the inclusion criteria were included. There were 325 students in the experimental group and 319 students in the control group, totaling 644 students. The quality of the study was evaluated according to the evaluation principles of the Cochrane Center for Evidence-based Medicine. RevMan5.4 software was used for Meta-analysis. The results showed that the flipped teaching method had a significant positive effect on the learning effect of students' physical education. Therefore, flipped teaching method can significantly improve the effect of physical education and physical performance, and is worthy of further promotion in physical education.

Keyword:Flipped teaching, Physical education curriculum, Learning effect, Meta-analysis

Yuan Li


Paper Title:Seismic Analysis of Multistorey Building with Shear Walls using ETABS Software

Abstract—

A load-bearing wall is a structural member intended to resist horizontal forces such as earthquakes, wind forces and seismic forces parallel to the wall’s plane and at the same time to bear loads. These are essentially deflections commonly provided in tall buildings to restrict a complete collapse of the building when subjected to seismic loads. For the seismic structure of the buildings, shear walls or RC structural walls are important seismic elements that provide resistance to lateral load by providing an efficient bracing system. Since the response of the building is governed by the characteristics of the shear wall, it is important to properly evaluate the response of the shear wall towards seismic activity. The RCC model, the shear wall, the damper model, and the shear wall with damper model can have different seismic performances. This analytical study investigates the effects of shear wall location in RCC structures based on ground displacement, ground displacement, ground shear forces, and foundation shear in high-rise buildings. Using the response spectrum method and the seismic intensity method, the behavior of the building as a function of the shear wall position is proposed. In this analysis, the effects of normal force, shear force, and bending moment on the variation at various points of the shear wall are also investigated using ETABS software.

Keyword: Shear wall, Response Spectrum Method, Seismic coefficient method, ETABS Software, Multistorey building

Prem Kumar V


Paper Title:Combined Impact of Metakaolin and Steel Fibre on the Mechanical Characteristics of Concrete

Abstract—

Concrete, a widely utilized natural material in construction, experiences substantial demand for raw materials in its production. Given the escalating costs and demand for these raw materials, there exists a pressing need to explore alternative and efficient materials. Notably, concrete exhibits inherent weakness in tension but possesses strength in compression. To enhance its tensile strength, steel fibers are introduced. Similarly, replacing cement with Metakaolin in concrete has demonstrated the potential for improved performance.This study investigates the combined impact of Metakaolin and steel fibers on the mechanical properties of concrete. Metakaolin and steel fibers constitute the primary materials employed in this research. Various destructive tests, including compression, split tensile, and flexural tests, are conducted, alongside a non-destructive test using ultrasonic pulse velocity to assess concrete quality. The study examines the individual and combined effects of both materials on the mechanical properties of concrete. The test results indicate a discernible enhancement in the mechanical properties of concrete with the incorporation of Metakaolin and steel fibers.

Keyword: Metakaolin; Steel fibres; Compressive strength; Split tensile strength; Flexural strength; Non-destructive testing

Prem Kumar V


Paper Title:Research on Nurses’ Psychological Empowerment: A Bibliometric Analysis

Abstract—

Psychological empowerment is a cultural, social, or psychological process that enhances individual control and autonomy over thoughts, emotions, and behaviors by developing attributes like self-identity, autonomy, and self-efficacy, which are integral to success in modern organizational management, particularly in service sectors like nursing. This study aimed to analyze the study focus, thematic trends, and evolution of studies on nurse psychological empowerment by using bibliometric analysis. The articles on nurses' psychological empowerment were obtained from the Web of Science Core Collection (WOSCC) database from its inception to November 30, 2023. The R package “bibliometrix” was used to conduct the data analysis and graphical presentation. A total of 188 publications on nurses' psychological empowerment were included. Publications were mainly from the USA, Canada, and China. The most frequent keywords included “empowerment”, “psychological empowerment”, “nurses”, “nursing”, “job satisfaction”, “structural empowerment”, “burnout” and “leadership”, the most frequent topics were “power”, “settings”, “work satisfaction”, and “turnover”. This bibliometric analysis identified the research trend of nurses’ psychological empowerment in the past 25 years, and this subject has already become an active field of study in nursing research. In addition, nurse retention-related themes such as job satisfaction, and work environment have become hot topics in current research while structural equation model-based themes have been less studied.

Index Terms: bibliometric analysis, nurse, network analysis, psychological empowerment

Liebin HUANG


Paper Title:Experimental Investigation on Utilization of Substitute Building Materials in Concrete Using Neural Networks

Abstract—

One of the most frequently used building components worldwide is concrete. The replacement of Cement with Sugarcane bagasse ash is considered due to its rich properties of projecting pozzolanic activity. The availability of aggregates is becoming scarce as a result of the non-renewable characteristic of fine and coarse aggregates. The replacement of aggregates from industrial waste by-products is necessary to maintain and make safe disposal in the present world. The construction waste end products like demolishing waste also cause the problem of improper disposal. Hence a majority of the construction industries have preferred the usage of Construction and Demolition waste as a replacement for Coarse aggregate. Substitution of coarse aggregates by Construction and Demolition waste and fine aggregates by iron slag ash is considered. The Taguchi method is adopted for the determination of mix combinations. This paper focuses on determining the Properties of Sustainability concrete having pozzolanic properties by replacing the cement with sugarcane bagasse ash (SBA), coarse aggregate with demolished building waste (DBW), and Fine aggregate with iron slag ash (ISA). The experimental investigation proved that SBA, DBW and ISA have a potential sign to be used as an alternative sustainable building material. From the comparative analysis of experimental results with ANN, it is revealed that the concrete show an acceptable prediction of physical and strength properties.

Keywords: Sustainability, Sugarcane bagasse ash, Iron Slag, Construction and Demolished Building Waste, ANN.

Prem Kumar V


Paper Title:An experimental study on the impact of martial arts routine learning on executive functions of 7 - 8 years old female children

Abstract—

Executive function is one of the essential components of human cognitive function. Studies have found that improving executive function has a better impact on children’s academic achievement, behavioral performance, and mental health. This study employed an experimental design to investigate the effects of different types of motor learning on the development of 7-8-year-old children's executive functions. The intervention was the Wushu routine learning; sample size was 37 female children (experimental group 23, control group14), mean age was 7.38 years. The study applied the psychological experimental research software E-prime 2.0 developed by Psychology Software Tools, Inc. to evaluate the experimental groups' inhibitory function, refreshing function, and conversion function level by completing the Flanker task, 1-back task, and more-odd shifting task. The results showed that the intervention effect of motor learning was mainly manifested in the conversion function, while it had no significant effect on the inhibitory function and refreshing function. Different intervention duration of motor learning did not have significantly different effects on executive function.

Keywords: Executive Function, Female children, Wushu routine learning

Chon Ieng Ho


Paper Title:Fulfilling K-12 Students' Mathematics Needs: Near Peer Teaching and Scientific Intelligent Clustering Tutor Approach

Abstract—

This investigation delves into the pressing need for curriculum reform in Indonesia, specifically examining the "Merdeka Belajar: Kampus Merdeka (MBKM)" policy, with a focus on the Near Peer Teaching (NPT) model. Previous studies have flagged NPT's shortcomings, attributing them to inconsistent tutor feedback rooted in relational challenges. Despite positive anecdotal evidence of student transformation through NPT, such accounts often lack objectivity. This research strategically surveys K-12 vocational schools in Kuningan, honing in on challenges in Mathematics to inform responsive teaching strategies. Noteworthy is the persistence of selecting peer tutors based on final exam scores, a practice upheld despite the initial randomness in NPT tutor selection, creating hurdles in gauging effectiveness. Paradoxically, empirical data suggests that third-semester students make better tutors, yet the fixation on final exam scores persists. To propel the NPT model forward, the study advocates for clustering tutors based on scientific intelligence, using a comprehensive approach that melds quantitative data science with qualitative Deep Interviews.The crux of the findings revolves around the imperative to refine the selection process for peer tutors. This entails considering factors such as interest, motivation, and academic achievement to significantly amplify the efficacy of NPT within the learning environment.

Keywords: Machine Learning, Near Peer Teaching, Aledu, K-12.

Ibnu Nur Akhsan


Paper Title: AI Value Creation: Operational value creation potential of semantic AI assistants in corporate training

Abstract—

Between March and May 2023, the AI Education (AIEDN) research project investigated the impact of a semantic AI-based learning assistant on students' learning processes. This assistant, designed to improve comprehension through video-based learning, was tested on 275 students aged 14-20 from two secondary schools and two grammar schools in Baden-Württemberg, Germany. The study aimed to determine whether the learning assistant helped students complete more tasks, develop broader knowledge (including transfer knowledge), and retain this knowledge effectively. The assistant interpreted questions using semantic AI and provided relevant excerpts from maths YouTuber Daniel Jung's videos. The results showed that the AIEDN AI learning assistant significantly improved the students' learning performance. The results of our research inspired our team to explore the potential value of semantic artificial intelligence (AI) in corporate training. Drawing on insights from 12 qualitative interviews with HR professionals and freelance trainers, our study explores the impact of AI on training methodologies. The results show that AI significantly improves the quality of learning materials, promotes personalisation and streamlines the learning process. It facilitates tailored, self-directed learning on demand, highlighting a synergistic blend of technology and human mentorship as a forward-looking approach. This underlines the growing importance of AI in corporate training environments. However, implementing AI-based learning assistants has challenges, including privacy, IT security and acceptance of AI technology. Semantic AI, with its ability for natural language interaction and improved understanding of content at a semantic level, leads to improved user experience and more effective information retrieval. These findings highlight the potential of semantic AI in corporate training, which includes benefits such as time efficiency, increased effectiveness, cost reduction, skill enhancement and improved job performance. This could be critical in addressing current business challenges and strengthening competitiveness in an evolving global landscape. However, the specific benefits will depend on individual organisational contexts. In summary, semantic AI holds great promise for adding value to corporate training programmes. However, addressing privacy and user acceptance issues will be critical to its implementation. Future research should further investigate the long-term implications of semantic AI in this area.

Keywords: Continuing education, corporate training, artificial intelligence, education technology, semantic AI, value creation, learning analytics, user experience

Alica Sailer


Paper Title: Implementation of Audio MOOC Book on Flipped Classroom to Enhance English Learning

Abstract—

Traditionally learning English has limited learning time and learning media. So a Flipped Classroom model is needed that allows students to study anytime and anywhere before learning activities in face-to-face classes. To implement the Flipped Classroom, interactive learning media is needed, therefore it is proposed to integrate the Audio Massive Open Online Course (MOOC) Book in the Flipped Classroom to improve student learning outcomes in English. The integration of audio and quiz-based content in the Flipped Classroom MOOC aims to provide a dynamic and accessible learning experience, encouraging increased language proficiency and increased student engagement. This article describes the design, implementation, and assessment of this innovative pedagogical approach. Preliminary findings indicate a positive correlation between the use of Audio MOOC Books and improved English learning outcomes, thus highlighting the potential benefits of combining online learning resources with the Flipped Classroom model in the context of English education. This research is expected to improve students' ability to pass the TOEFL test with a high score, so that they can qualify for higher education scholarships.

Keywords: audio mooc book, flipped classroom, english learning.

Haris


Paper Title: The Influence Of Prices Of Vegetable Imports From China And The Number Of Indonesian Population On The Volume Of Indonesian Vegetable Imports From China For The Period 2010-2022

Abstract—

Vegetable production which is lower than the population's needs encourages Indonesia to import from China which is superior in terms of price and quality. The research aims to determine how much influence the price of Indonesian vegetable imports from China and the Indonesian population have on the volume of Indonesian vegetable imports from China partially and simultaneously. The research method uses quantitative and qualitative data through multiple regression equations during the period 2010-2022. The calculation results show that there is a negative and significant relationship between import prices and the volume of Indonesian vegetable imports from China. Vegetables are normal goods that are essential for health so they must be available in large volumes and at low prices. The population of Indonesia is positively and significantly related to the volume of Indonesian vegetable imports from China. The main factor is the large population creating high purchasing power for imported vegetables from China. Simultaneously, these two independent variables have a significant effect on the volume of Indonesian vegetable imports from China. From a microeconomic perspective, import volume is greatly influenced by low prices of goods and Indonesia's large population. The solution that must be implemented is collaboration between related parties to make vegetables a source of people's welfare.

Keywords: vegetable imports, prices, population, import volume

Sugiartiningsih


Paper Title: Development of Speaking Training Media Based Android Application for Beginner BIPA Learners

Abstract—

Darmasiswa program is an Indonesian language learning program for foreign speakers. In this program, students are introduced to Indonesian language and culture. Beginner level BIPA learning in the program still finds problems related to teaching materials on speaking skills. Based on these problems, there is a need for the development of media for practicing speaking skills. The media aims to enable students to practice speaking independently without the need to be accompanied by a teacher or native speaker. The development of the training media can answer the formulation of problems related to the feasibility of content, language, and presentation systematics. The ADDIE model was used in this development. Based on the validation of speaking training media, the results obtained (1) material validation resulted in a good category, (2) language validation resulted in a good category, (3) media validation resulted in a very good category, and (4) practitioner validation resulted in a very good category. Based on this validation, the android-based speaking skill training media can be implemented for beginner BIPA students so that it produces an excellent category. This makes this speaking training media easier for beginner-level BIPA students in meeting the competency standards of beginner-level speaking skills.

Keywords: training media, speaking, android, BIPA, and beginners

M. Fernanda Adi Pradana


Paper Title:The Influence Of Eco-efficiency, Carbon Emission Disclosure And Green Innovation On Company Value (case Study Of A Basic Materials Sector Company Listed On The Indonesia Stock Exchange For The 2018-2022 Period)

Abstract—

Economic growth is developing rapidly, marked by the development of the industrial world in recent years. In line with the development of the industrial world, issues regarding environmental pollution such as global warming and carbon emissions are also developing. The aim of this research is to find out how eco-efficiency, carbon emission disclosure, green innovation affects company value. The method used is quantitative, using secondary data. The sampling technique used purposive sampling to obtain 17 companies with 5 years of observation from 2018-2022 in basic materials sector companies listed on the Indonesian Stock Exchange (BEI) so that 85 data were obtained. Data processing uses SPSS version 25 with descriptive statistical analysis methods. This research shows that eco-efficiency and carbon emission disclosure have no effect on company value, while green innovation has a positive and significant effect on company value and simultaneously eco-efficiency, carbon emission disclosure and green innovation have an effect on company value. It can be concluded that eco-efficiency and carbon emission disclosure cannot reduce the environmental impact caused by the company's operational activities, but green innovation has proven successful in carrying out innovations or modifications in reducing the impact of environmental damage and means that the company has complied with the normal social norms that exist in society. related to the environment.

Keywords: Eco-Efficiency, Carbon Emission Disclosure, Green Innovation, company value

Lisna Rahmawati


Paper Title:Augmented Reality in E-Commerce: A Comprehensive Systematic Literature Review and Future Directions

Abstract—

Augmented reality is a technology that is now being widely adopted by the e-commerce sector. Research that comprehensively discusses the trends and impact of augmented reality on e-commerce is still not widely available. Therefore, the aim of this research is to overcome these limitations by providing an in-depth understanding of the trends and impact of augmented reality in e-commerce. Another aim is to provide gaps and contribute to opening up future research opportunities, as well as providing recommendations regarding the application and optimization of augmented reality technology in e-commerce business strategies. This research used the Systematic Literature Review method with the selected articles totaling 36 out of 592 articles. Of the 36 selected articles, the author presents findings which show that the current trend of augmented reality used in e-commerce is virtual try-on, preview placement and social media filters, as well as presenting the impact of using augmented reality as seen from user experience, satisfaction and consumer behavior. This research also presents gaps, future research and recommendations that are useful for the e-commerce sector.

Putri Sri Munajat


Paper Title:Employers Feedback on the Performance of the College of Computing Studies, Information and Communication Technology (CCSICT) Graduates

Abstract—

This study is an assessment of the employer’s feedback on the performance of College of Computing Studies, Information and Communication Technology (CCSICT) graduates in the workplace with respect to quality and quantity of work, job knowledge, and working relationships. The study used a descriptive research method utilizing the employers of employed graduates as key informants. The respondents were purposely chosen who are managers or supervisors of companies and institutions of the graduates. Data from the 98 employers were gathered using a survey questionnaire. Weighted mean, frequency count, percentage, and rank were used to interpret the result of the survey. Results showed that graduates are employed in the Information and Communication Technology (ICT) industry. This means that the graduates have jobs related to their course. The majority of employers who participated in the survey are from the private sector. Employers were very satisfied with the graduate's quality and quantity of work, job knowledge, and work relationship. The top attributes used to evaluate the graduates' performance were the quantity of work and the working relationships. The findings suggested putting emphasis on written and oral communication skills and improving networking, troubleshooting skills, and graphics and design skills.

Keywords: Information Technology, feedback, employers, Performance, employer satisfaction

Rosemary L Buraga


Paper Title:Digital farmer’s profiling system for decision support towards e-governance

Abstract—

The "Digital Farmer's Profiling System for Decision Support in E-Governance Research" is an innovative approach harnessing digital technologies to elevate the realms of agriculture and governance. Its primary objective was to create an integrated digital profiling system for farmers, enabling the collection and analysis of essential farmer data, thereby facilitating informed decision-making for both farmers and departmental agriculture offices. Specifically, the project aimed to develop a profiling system with distinct components, including farmer profiles, land profiles, livestock and poultry information, aquaculture farmer data, service provider details, livelihood insights, and cost and return analysis information. Additionally, the system features an efficient reporting mechanism capable of generating critical information, such as lists of farmers and land forecasting data. The research employed a qualitative methodology, gathering data from sample documents and interviews involving registered farmers and agricultural stakeholders, selected through a stratified sampling approach to ensure diversity in geographical locations and farm types. Ethical considerations, including a rigorous commitment to data privacy and obtaining informed consent, were meticulously observed throughout the research process. The Agile software development model was employed for designing and developing the system. This study has not only successfully met all the requirements of a farmer's profiling system with an exceptional capability by encompassing key components. Furthermore, it features a robust reporting mechanism for generating crucial data, including lists of farmers and land forecasting information.

Keywords: profiling system, farmers information, database system for farmers.

Rosemary L Buraga


Paper Title:Enhancing Security through Predictive Analytics and Anomaly Detection in IoT-enabled Systems

Abstract—

The framework that uses sophisticated deep learning algorithms and data preparation to improve anomaly detection in Internet of Things systems. In order to standardize location coordinates and minimize the computational load on the network, the first data transformation uses Min-Max normalization. Next, it is shown how to use Principal Component Analysis (PCA) to efficiently reduce dimensionality while maintaining important information in high-dimensional datasets that are frequently used in Internet of Things applications. The process of standardization in principle component analysis (PCA) guarantees fair feature contributions. The covariance matrix is then computed, which makes it easier to extract principal components and capture the maximum variance in the data. Additionally, by using CNNs' ability to autonomously learn hierarchical representations straight from pictures, the paper suggests integrating CNNs for image-based anomaly identification. The CNNs are very good at identifying abnormal from normal patterns across a wide range of domains because they use transfer learning and encoder-decoder architectures to capture complex patterns. With accuracy of 90.91%, recall of 87.9%, F1-score of 90.3%, and a ROC value of 95%, the proposed CNN model shows encouraging results, highlighting its resilience in anomaly identification. Looking ahead, the area of work includes improving methods for detecting anomalies through creative pretreatment of data and fine-tuning CNN structures to make them more flexible in the face of changing Internet of Things scenarios. The investigation of ensemble methods and reinforcement learning offers further opportunities to boost anomaly detection systems' accuracy and robustness. Overall, this study offers a thorough and practical method for IoT anomaly detection, adding to the changing field of intelligent and connected devices.

Keywords: Anomaly Detection; Min-Max Normalization; Principal Component Analysis; Convolutional Neural Networks; Dimensionality Reduction

Zaheer sultana


Paper Title:Design of a Scientific Literature Recommendation System for Optimizing On-time Graduation of Students Using a Combination of Latent Semantic Analysis and Latent Dirichlet Allocation Text Mining Methods

Abstract—

This study was conducted to evaluate the effectiveness of the Latent Dirichlet Allocation (LDA) method in extracting keywords from scientific article abstracts in Scopus, Elsevier, and Science Direct, highlighting the challenge of obtaining accurate and relevant information. To enhance text extraction performance, this research combined LDA with Latent Semantic Analysis (LSA), methods typically used separately. The method was tested through cosine similarity comparison and keyword overlap between extraction results and manual extraction, GPT-4, Scopus, and author keywords, as well as through a web application used by UNDIP alumni and students. The results showed that the combined method provides more diverse keyword insights compared to LDA alone, without adding significant computational load. Therefore, this combined approach offers a more comprehensive method for keyword extraction in scientific research.

Keywords:Latent Dirichlet Allocation, Latent Semantic Analysis, Keyword Extraction, Text Analysis, Cosine Similarity

Pasha Dwi Mahendra


Paper Title: ADAS for Indian Roads

Abstract—

The "Development of Advanced Driver Assistance Systems (ADAS) for Indian Roads" project endeavors to optimize and expand existing ADAS functionalities to align with the specific challenges posed by Indian traffic conditions. Focused on enhancing road safety and driving comfort, the project encompasses three critical modules: Traffic Sign Recognition (TSR), Driver Monitoring System (DMS), and Pothole Detection, all powered by the real-time capabilities of the state-of-the-art YOLOv8 object detection model. By leveraging YOLOv8's capabilities, the project aims to address the intricacies of recognizing diverse traffic signs, monitoring driver behavior in real-time, and detecting potholes on Indian roads.

Index Terms— :Advanced Driver Assistance Systems (ADAS), YOLOv8, Traffic Sign Recognition (TSR), Driver Monitoring System (DMS), Pothole Detection, Object Detection, Real-time Processing

Hemachandran S


Paper Title: A systematic review of the impact of open and closed sports interventions on executive function in individuals with ADHD

Abstract—

Attention Deficit Hyperactivity Disorder is one of the most common childhood psychiatric disorders, with a global prevalence estimated at 3.4%. In recent years, the impact of physical activity on the executive function (EF) of children, especially those with cognitive impairments, has garnered increasing attention from scholars, leading to a steady stream of research findings. Some scholars have conducted systematic reviews and meta-analyses of such research outcomes. While open motor skills are considered to offer advantages in enhancing EF in typical children, their impact on individuals with ADHD is not yet fully understood. This study aims to explore the impact of closed and open motor skills on the EF and its sub-functions in individuals with ADHD through a systematic review. According to the PRISMA guidelines, a search was conducted across seven databases, including PUBMED, EMBASE, Cochrane Library, for evaluation and analysis. A total of 27 articles were included, comprising 22 articles on interventions involving closed motor skills and 5 articles on interventions involving open motor skills. The results indicate that both closed and open motor skills interventions have a positive impact on the EF of individuals with ADHD. However, the improvement in the sub-function of working memory is relatively weak

Keywords :attention deficit hyperactivity disorder, executive function, Open skill, Closed skill

Chunyue Qiu


Paper Title: Twitter, Instagram, Youtube Speak: Understanding Sentiments on LRT Jabodebek Services via Inset Lexicon, IndoBERT and BERTopic Approaches

Abstract—

Rapid urbanization in the Jabodetabek region has led to an increased demand for public transportation. Responding to this need, the government has initiated the development of a new public transportation mode, namely the LRT Jabodebek. However, as a new public transportation mode, the LRT Jabodebek has both strengths and weaknesses in serving the community. Various public comments are expressed through social media platforms. To enhance service quality, it is crucial to pay attention to public comments. Therefore, a sentiment analysis is required to identify and delve into both positive and negative sentiments regarding the LRT Jabodebek service through comments on Twitter, Instagram, and Youtube. The methodology involves a combination of Lexicon-based, IndoBERT model, and BERTopic approaches to gain a deeper understanding of the Jabodebek LRT service trends. The study reveals that 55.9% of the 8,523 comments carry a negative sentiment, and the IndoBERT model achieves an accuracy of 85.97% in sentiment classification.

Keywords :IndoBERT, BERTopic, Lexicon-Based Approach, Light Rail Transit.

Ibadurrohman Irfan Fatani


Paper Title:The knowledge management of the university in the digital age: towards a model based on Karl Wiig's approach in 1986.

Abstract—

This article examines the optimization of knowledge management through digital technology in Moroccan universities. We utilized a research methodology based on a review of theoretical literature. Drawing on Wiig's 1986 approach as a conceptual foundation, we used it as a starting point for a thoughtful integration of digital technological resources and artificial intelligence capabilities. The objective is to provide support to higher education institutions in knowledge management by creating an environment conducive to dynamic interaction and progressive learning for both students and teachers. The early stages of a higher education model focused on digital knowledge management already demonstrate the significant value of this approach, thus opening promising prospects for future advancements in the field of higher education

Keywords :Artificial intelligence, Digital technology, Higher education, Knowledge management.

Sibari Hala


Paper Title:The Moderating Effect of Business Environment on the Supply Chain Management Practices and Competitive Advantage of the Chinese Construction Industry in Kunming, The People's Republic of China

Abstract—

The purpose of this study was 1) to study the importance level of supply chain management practices, business environment, and competitive advantage of construction enterprises, 2) to study the effect of supply chain management practices, and business environment toward the competitive advantage of the Chinese construction enterprises, and 3) To test the moderating effect of the business environment on the supply chain management practices and competitive advantage of the Chinese contraction industry in Kunming, the People's Republic of China. It is quantitative research. The sample consisted of 350 business owners registered with the Kunming City Commercial Office, China in 2023. The research tool is an online questionnaire. Collect data through websites, WeChat, and applications. Data were analyzed by descriptive statistics including mean and standard deviation. Inferential statistics were analyzed with SEM. The results showed that all factors were very high important. It should be arranged from the most important to the least important. including competitive advantage (4.55), business environment (4.52), and supply chain management practices (4.46). The result of the effect of supply chain management practices had a direct effect on competitive advantage, with a path coefficient equal to 0.829, followed by the business environment, is the moderating effect of supply chain management practices to competitive advantage, with a path coefficient equal to 0.007. The results of a study moderating the effect of the business environment on supply chain management practices and competitive advantage were found to be statistically significant at the 0.01 level. This means that the Chinese construction industry must consider the business environment, especially since external conditions can be unpredictable and can impact their competitive advantage in Kunming.

Keywords :Business Environment, Supply Chain Management Practices, Competitive Advantage, The Chinese Construction Industry

Linxin Yang


Paper Title:The Optimal Configuration of Charging Piles for New Energy Vehicles in Shizong County: An Investigation

Abstract—

The purpose of this study was 1)Based on the existing number and location of public charging piles in ShizongCounty, this study explores the problems existing in the configuration of public charging piles in Shizong County,2)Explore the views of residents in Shizong County on new energy vehicles, so as to determine the demand for public charging piles,3)Combined with the local traffic situation and urban development planning, explore the optimal configuration scheme of public charging piles in ShizongCounty, and obtain suggestions on the reasonable setting of public charging piles.This research tool is a paper survey questionnaire. After-sales service interview survey was conducted on 250 new energy vehicle owners in Shizong County through a new energy vehicle sales terminal (4S store). Starting from the actual use scenarios of new energy vehicles, the interests of both charging station operators and new energy vehicle users were considered, including construction costs, operation and maintenance costs, network loss costs, user consumption costs, user loss costs, and land use costs, We constructed a goal programming model that minimizes the total social cost and used an improved particle swarm optimization algorithm to solve it. The results indicate that the optimal layout plan for public charging piles for new energy vehicles in Shizong County. Ontheonehand, this plan demonstrates the reliability and rationality of the constructed model system theory, and on the other hand, the research results provide reference for the development decision-making of the new energy vehicle industry in Shizong County, assisting in the construction of new energy charging facilities, thereby promoting the development of the new energy vehicle industry inShizongCounty, making the research both theoretical value and practical significance.

Keywords :New energy vehicles,Public charging station,optimized layout,Particle.

Wenchao Zhou


Paper Title:The State Of Teacher Training In The Conditions Of Dual Training

Abstract—

The purpose of this article is to understand and justify the conditions for the use of elements of the dual training system in the implementation of professional educational programs to improve the efficiency and quality of training of qualified pedagogical personnel in secondary education institutions. The article discusses the advantages and disadvantages of dual education as a technology for preparing bachelor's degree programs in modern conditions of pedagogical university. Nowadays the topic of "dual training" is a very urgent problem on the pedagogical platform. Because vocational education has never been conceived without connection with the manufacturing sector. The authors describe how dual education is carried out abroad, as well as how the dual education model is being implemented in Kazakhstan. As an example to describe the introduction of elements of dual training, the system of dual training of some pedagogical universities of the Republic of Kazakhstan is presented. The article shows that this technology makes it possible to solve the tasks assigned to the pedagogical university for the training of pedagogical personnel for the system of secondary vocational education. Dual training reduces the gap between theory and practice, promotes the professional development of teaching staff. In addition, it sets new tasks for the higher education system: the development of dual training programs, the regulation of tripartite relations "university – student – employer".

Keywords :Training of teachers, dual training, professional pedagogical education, school, higher educational institution

A.A. Seitalieva


Paper Title:The Determinants of Core Competitiveness Toward Firm Performance of Construction Enterprises in Kunming, the People's Republic of China

Abstract—

The purpose of this study was 1). To study the importance level of factor conditions, demand conditions, government, firm strategy, structure, rivalry, related and supporting industries, and chance events of construction enterprises in Kunming, and 2). To analyze determinants of core competitiveness toward the firm performance of construction enterprises in Kunming, The People's Republic of China. It is quantitative research. The sample consisted of 400 enterprise owners registered with the Kunming City Commercial Office, China in 2023. The research tool is an online questionnaire. Collect data through websites, WeChat, and applications. Data were analyzed by descriptive statistics including mean and standard deviation. Inferential statistics were analyzed with Multiple Regression by Enter Selection. The results showed that all factors were high important. It should be arranged from the high important to the least important. including supplier power (3.90), threat of new entry (3.88), buyer power (3.87), firm performance (3.85), competitive rivalry (3.80) and threat of substitution (3.78). The result of the effect of supplier power had a direct effect on firm performance, with a path coefficient equal to 0.509, followed by the threat of new entry had a direct effect on firm performance, with a path coefficient equal to 0.297, the competitive rivalry had a direct effect on firm performance, with a path coefficient equal to 0.089, the threat of substitution had a direct effect on firm performance, with a path coefficient equal to 0.079, and Lastly, buyer power entry had a direct effect on firm performance, with a path coefficient equal to 0.071. Except for the threat of new entry, which had a direct effect on firm performance with a path coefficient equal to 0.297, none of the other variables were statistically significant at the 0.10 level.

Keywords :Determinants of Core Competitiveness, Firm Performance.

Haoyue Deng


Paper Title:Survey on Methodologies to Implement Automated Data Entry using Smartpen

Abstract—

In an era of digital transformation, efficient and accurate data entry remains a critical challenge, from healthcare to logistics. In many scenarios like an application form, filling the data using pen and paper is a more viable option. Considering this, the survey delves into the realm of automated data entry using smart pens, a novel technology at the intersection of handwriting recognition, computer vision, and the Internet of Things. Furthermore, it delves into the intricacies of character recognition algorithms and explores the potential of machine learning and deep learning in enhancing the accuracy of recognition. With a focus on user-centric design, we examine user experiences and the integration of smart pens into existing workflows. Additionally, the paper delves into security and privacy considerations, shedding light on the safeguarding of sensitive data. Through a synthesis of current research and practical implementations, it aims to provide a roadmap for researchers, developers, and industry stakeholders to harness the transformative power of smart pens in automating data entry processes, ultimately leading to increased productivity and data accuracy in a digitally driven world.

Keywords :Smart Pen, Handwriting Recognition, Computer Vision, Internet of Things (IoT), Data Entry, Digital Transformation, Character Recognition, Machine Learning, Deep Learning.

Jayakshata PR


Paper Title:Realistic Face Image Generation With Age and Ethnicity prediction for criminal identification

Abstract—

Criminal investigation and identification are critical components of law enforcement that rely heavily on the accuracy and reliability of physical evidence, witness statements, and other sources of information. One such source is facial composite drawings, which are hand-drawn sketches of suspects created by eyewitnesses or victims. These sketches are drawn by professional artists. However, these sketches are often incomplete, inaccurate, or inconsistent, making it challenging for law enforcement agencies to identify suspects accurately. Attributes like age and ethnicity can be predicted from the sketch only if the quality of the sketch drawn is great. This leads to the requirement for an image generator which takes sketches as input. The development of a realistic face image generator from sketches using Generative Adversarial Network(GAN) presents a potential solution to this problem. This model can be used to convert hand-drawn sketches to lifelike images using it’s key components: Generator and Discriminator. The model is integrated with other essential models which help in predicting age and ethnicity of the image generated using Generative Adversarial Network(GAN). The age and ethnicity prediction can be developed using Convolutional Neural Networks(CNNs). Using these models, law enforcement agencies can more accurately identify and compare suspects to databases of known individuals, increasing the efficiency and accuracy of criminal investigations.

Keywords :Generative Adversarial Network(GAN), Convolutional Neural Network(CNN), Age and Ethnicity Prediction, Generator, Discriminator

K Vasanth Karthik


Paper Title:Improving Communication Idea and Information, Problem Solving Skill Through Problem Based Learning

Abstract—

The objectives of this paper were to develop the problem based learning in a project course for improving communication idea and information, problem solving skill for actual work in the workplace. Starting from analysis, design, development, implement and evaluation of problem based learning, identification of population and sample, implementation of problem based learning in project course for actual work in a workplace that was designed, with Phradabos’s students who study in the project course I, and then collect data, analysis and conclusion. The result found that the competency was good level, the efficiency of problem based learning in project course was 83.30/82.13 that were above 80/80 established criteria, the advanced abilities after learning of students who learned from problem based learning in project course increased more than before learning, a knowledge and abilities of students were improved, the amount of students passing the project course I was 68.42%, which is higher than the previous time and almost project workpieces can meet industrial requirements.

Keywords :Communication idea and information, problem solving, competency, skill, problem based learning.

Chokchai Alongkrontuksin


Paper Title:Identifying Critical Elements to Enhance Undergraduate Students' Online Learning Practices in Thailand

Abstract—

This study is quantitative. Determine the critical elements that influence the improvement of online learning behavior among Thai undergraduates. It proposes methods to enhance the efficiency and effectiveness of learners' learning by utilizing essential aspects derived from the research. The sample for this study consisted of undergraduates. A multi-step randomization mechanism is employed. To assess multiple regression analysis, employ statistical analysis. This study identified four significant determinants that influence the formation of online learning behavior: 1) The environment in the vicinity. 2) Occasional circumstances. 3) Capability to regulate behavior while learning online. 4) Support from family members. The researcher concluded the study by presenting strategies for cultivating online learning habits to enhance the efficiency of online learning.

Keywords :Online Learning, Undergraduates

Naksit Sakdapat


Paper Title:Assessment of Transmission Protection for Electricity Reliability in Kalimantan

Abstract—

PT PLN (Persero) is a State-Owned Enterprise, which is engaged in the electricity sector, Main Generation and Transmission Unit which manages the Generation and Transmission in Kalimantan called UIKL KAL. The transmission configuration of the long overhead line stretching from North, East, South, and Central to West Kalimantan with forest topography of hills and ravines has a high risk of disturbances causing huge losses for both PLN and customers. The maintenance has been carried out according to existing procedures. However, the failure of the protection function to localize these disturbances is still frequent and even causes widespread and prolonged outages. Hence, it is necessary to identify the causes of frequent and large-impact transmission disturbances and a new method using Fault tree analysis and multi-linear regression that is better for ensuring the readiness of energy security to improve reliability and performance. By finding a strong correlation between each type of disturbance to the performance of the Auto Reclose Index, it was found that the disturbance by the tree caused the Auto Reclose Index performance to be very low and it was found that disturbance by lightning and kites caused the Auto Reclose Index performance to be very high

Keywords :assessment, protection, transmission, reliability, regression, disturbance

Ervin Saputra, S. Tr.T. M.MT.


Paper Title:Effect of Quick Response and Supply Chain Efficiency toward Customer Satisfaction to Use Express Delivery Company in Kunming, People's Republic of China.

Abstract—

The purpose of this study was 1) to study the importance of quick response patterns and supply chain efficiency and customer satisfaction, 2) to analyze the impact of quick response and supply chain efficiency, on customer satisfaction, and 3) to model the causal factors influencing the quick response and efficiency of the supply chain on customer satisfaction using express delivery companies in Kunming, China. It is quantitative research. The sample consisted of 400 customers who have used the express delivery company approach. The research tool is an online questionnaire. Collect data through websites, WeChat, and applications. Data were analyzed by descriptive statistics including mean and standard deviation. Inferential statistics were analyzed with Path Analysis.
The results showed that all factors were very important. Sorted from most to least, including supply chain efficiency, quick response, and customer satisfaction. The result of quick response had a direct effect on customer satisfaction, with a path coefficient equal to 0.991, followed by quick response had a direct effect on supply chain efficiency, with a path coefficient equal to 0.341, Lastly, The effect of supply chain efficiency had a direct effect on customer satisfaction, with a path coefficient equal to 0.009. Therefore, for customers who prioritize supply chain efficiency and speedy service, express delivery companies should prioritize their quality of service. They need to have a supply chain system that connects with everyone involved to achieve maximum efficiency.

Keywords :Quick Response, Supply Chain Efficiency, Customer Satisfaction, Express Delivery.

Qihan Li

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