Journal of Mathematics and Computing Science
The Journal of Mathematics and Computing Science (JMCS) (e-ISSN: 0128-0767) is an open-access, international, peer-reviewed journal that employs a single-blind review process. The journal welcomes original submissions in all areas of mathematics and computer science. Importantly, JMCS does not charge any publication fees. JMCS is available at Google Scholar, providing authors with greater visibility and accessibility.
Determinants of Overweight and Obesity Among University Students: A Logistic Regression Analysis of Knowledge, Lifestyle, and Psychological Factors
Recent data from the Ministry of Health Malaysia (2023) reported that 54.4% of Malaysian adults are classified as overweight or obese, representing a 4.3% increase since 2019. The rising prevalence of overweight and obesity poses a significant public health concern, as these conditions are major risk factors for non-communicable diseases such as cardiovascular disease and diabetes, which remain among the leading causes of mortality worldwide. Despite this growing trend, empirical research examining the determinants of body mass index (BMI) among university students in Malaysia remains limited. This study aimed to examine the influence of knowledge, lifestyle, and psychological factors on BMI levels among university students. A cross-sectional survey was conducted among 316 students from two faculties at Universiti Teknologi MARA (UiTM) Kota Bharu using a structured questionnaire to assess these variables. The prevalence of overweight and obesity among the respondents was 23.4% and 11.4%, respectively. The findings indicated that knowledge and lifestyle factors were significantly associated with BMI status among university students. These results emphasize the importance of targeted health education and behavioral interventions to foster healthier lifestyles and mitigate the risk of overweight and obesity within the university population.
Copyright (c) 2025 NUR NISWAH NASLINA AZID MAAROF, Siti Nurani Zulkifli , Norafefah Mohamad Sobri, Nor Azima Ismail, Siti Zakiah Hanim Mohd Aminuddin, Wan Faizah Wan Yaacob https://creativecommons.org/licenses/by-sa/4.0
Factors Influencing User Satisfaction on Social Media Application Among Undergraduates
In Malaysia, social media usage is incredibly high among youth, with a large proportion actively engaging with applications such as TikTok, Instagram, WhatsApp and Facebook. They use these platforms daily and often spend several hours online. This study aims to investigate the factors (informativeness, entertainment, sociability and perceived convenience) that influence undergraduate students’ satisfaction with social media applications. A structured questionnaire was then distributed to 268 undergraduate students using simple random sampling. The data collected were then analysed using SPSS software, employing descriptive statistics and multiple linear regression analysis to address the research objective. The findings revealed that all four factors, informativeness, entertainment, sociability and perceived convenience significantly influence users’ satisfaction with social media applications. The findings may be helpful for future researchers and developers seeking to design more engaging and user-friendly social media platforms.
Copyright (c) 2025 Nur Syaliza Hanim Che Yusof https://creativecommons.org/licenses/by-sa/4.0
Components Analysis in Finite Mixture Model
Determining the appropriate number of components within a finite mixture model is a challenging issue in statistical modelling. This is because the inappropriate choice misinterprets the data and could lead to poor performance. For this purpose, this study will apply empirical data on energy consumption and exchange rate in Malaysia to determine the suitable number of components using the finite mixture model. This study applies Akaike Information Criterion and Bayesian Information Criterion model selection criteria for considering model adequacy. The results demonstrated that the log-likelihood increases as the number of components increases. Indeed, even Akaike Information Criterion still favoured more complex models. However, Bayesian Information Criterion reached a minimum value of three components, which resulted in choosing the most suitable model structure. These results also indicated that Akaike Information Criterion overestimates the number of components. However, Bayesian Information Criterion yielded a more parsimonious and interpretable solution. This study tries to give practical meaning to model selection in mixture modelling. This study also points out the effectiveness of Bayesian Information Criterion in identifying meaningful group structures when the data are heterogeneous.
Copyright (c) 2025 Athirah Nadiah Mohd Tajol Aurus; Seuk Yen Phoong https://creativecommons.org/licenses/by-sa/4.0
Determinants of Students’ Satisfaction in Online Distance Learning: A Multiple Linear Regression
This study aims to determine which factors (student-student interaction, student-content interaction, and student-instructor interaction) significantly influence students’ satisfaction in online distance learning. An online survey was conducted among students of Universiti Teknologi MARA Kelantan Branch, Kota Bharu Campus from semester 3 to semester 7. The data collected was analyzed by using multiple linear regression analysis. The findings reveal that student-student interaction, student-content interaction, and student-instructor interaction emerged as the significant factor that contributed to students’ satisfaction in online distance learning. The insights gained from this research can guide educators and institutions in enhancing their teaching strategies and course designs, ultimately leading to more engaging and effective learning experiences for students in both online distance learning and blended learning environments.
Copyright (c) 2025 Nurul Hafizah Azizan, Shamsunarnie Mohamed Zukri, Nor Hazreeni Hamzah, Nurul Bariyah Ibrahim, Nur Nur Safwati Ibrahim, Noor Zafarina Mohd Fauzi https://creativecommons.org/licenses/by-sa/4.0
A Multiple Linear Regression Analysis of Factors Influencing Job Satisfaction Among Employees in a Selangor-Based Company
This study aims to examine the factors influencing job satisfaction among employees at a company in Selangor. Job satisfaction is a critical component of organizational success, directly affecting employee motivation, retention, and productivity. The study focuses on demographics (gender, position, department) and four key factors (compensation and benefits, work-life balance, work environment, career development opportunities). A quantitative approach was employed using a structured questionnaire distributed among 169 employees across various departments and positions. The data collected were analysed using descriptive and Multiple Linear Regression (MLR). The overall job satisfaction score among employees was 9.3 with all departments stated job satisfaction mean scores above 8.0. Meanwhile all mean scores for the key factors were above 8.9. In the regression analysis, the variable compensation and benefits was excluded due to multicollinearity issues. The finding shows that factors (work-life balance, career development opportunities, position) significantly influenced the job satisfaction among employees. The study highlights the importance of addressing these issues to enhance employee engagement and organizational performance. Ultimately, the insights gained can assist management in formulating targeted strategies to improve workplace satisfaction and retain top talent. In conclusion, the study offers evidence that may support both managerial decision-making and future research on employee job satisfaction.
Copyright (c) 2025 SHAMSUNARNIE BINTI MOHAMED ZUKRI, Nik Nur Hasfawati Izlyn Nik Hassan, Noor Zafarina Mohd Fauzi, Nurul Bariyah Ibrahim, Ruhani Muhamad5 https://creativecommons.org/licenses/by-sa/4.0
A SELECTION OF COURIER SERVICE PROVIDERS AMONG STUDENT UITMCK USING FUZZY ANALYTICAL HIERARCHY PROCESS (FAHP)
Courier services are now a vital component of contemporary life, enabling timely delivery of goods and documents while supporting the fast growth of e-commerce. Students frequently utilize these services for both personal and academic objectives and their decision is heavily influenced by elements like cost, delivery time, and consistency. In order to assess and rank four courier service provider such as GDEX, J&T Express, Pos Laju, and Ninja Van among students at Universiti Teknologi MARA Kelantan Branch (UiTMCK), this study suggests using the Fuzzy Analytical Hierarchy Process (FAHP). Ratings for criteria and alternatives were provided by five experienced decision makers using a linguistic scale. Decision makers evaluate the criteria using triangular fuzzy numbers within the context of FAHP which enables them to handle uncertain decision situations. Subsequently the calculated fuzzy weights adjust the influence of each criterion. These criteria serve as evaluation bases for alternatives after going through normalization procedures. The evaluation was conducted based on four main criteria which are cost efficiency, tracking and traceability, delivery timeliness and order accuracy. The results indicates that J&T Express ranked as the most preferred courier service, followed by Ninja van, GDEX and Pos Laju. Cost efficiency was identified as the most significant criterion, suggesting that pricing remains the primary consideration among student users. FAHP helps to deal with uncertainty in decision making, making it suitable for evaluating complex criteria.
Copyright (c) 2025 Wan Nurul Husna Wan Nordin, Nur Jesnita Junera Luxman Alhakim, Masnira Ramli, W. Nurfahizul Ifwah W. Alias, Aimi Zulliayana Rosli https://creativecommons.org/licenses/by-sa/4.0
Deciphering the Underlying Determinants of Money Management Among Undergraduate Students
Financial hardships are a prevalent challenge among university students, often hindering their academic performance and overall well-being. This study investigates the key determinants influencing money management behavior among students at a selected university in Negeri Sembilan, emphasizing the pivotal role of financial literacy in shaping financial decision-making. Utilizing a convenience sampling approach, data were collected from a sample of 372 students. Multiple linear regression analysis, using IBM SPSS Statistics Version 26, was employed to examine the relationships between the independent variable, namely, financial literacy, economic, social, and psychological factors—and the dependent variable, money management behavior. The findings indicate that economic (p-value = 0.010), social (p-value = 0.000), and psychological factors (p-value = 0.000) significantly influence students' money management behavior, while financial literacy does not have a statistically significant impact. These results highlight the need for educational institutions to implement targeted financial education programs that address not only financial knowledge but also the broader psychological, social, and economic factors affecting students’ financial decisions. By fostering a comprehensive understanding of financial management, universities can empower students to develop responsible financial habits, ultimately enhancing their financial stability and academic success. This study contributes to the growing discourse on student financial well-being and underscores the importance of multidimensional approaches in addressing financial challenges in higher education.
Copyright (c) 2025 Nabila Mohamad ’Asri , Nurul Najwa Afiqah Yuszaini , Az’lina Abdul Hadi , Nornadiah Mohd Razali , Siti Aishah Mohd Shafie, NUR NISWAH NASLINA AZID MAAROF https://creativecommons.org/licenses/by-sa/4.0
TECH-CLASS: A Geofencing-Driven Attendance Management System for Higher Education
Reliable and verifiable attendance monitoring continues to be a significant difficulty in higher education, as traditional manual and digital solutions are susceptible to fraudulent attendance and administrative inefficiencies. This study introduces TECH-CLASS, a geofencing mobile attendance system that automates the validation of physical presence through location-aware triggers. The system, developed with Android Studio, Google’s Geofencing API, and Firebase Realtime Database, underwent evaluation via functional testing and a System Usability Scale (SUS) assessment with 50 students at UiTM Machang. The results indicate a SUS score of 95.2 and a complete correspondence of 100% between geofence-triggered detection and verified in-class presence. The system's innovation is attributed to its adaptive geofence setup, integration of academic-specific workflows, and real-time synchronisation, which are absent in current institutional or prototype solutions. Recognised constraints encompass indoor GPS inconsistency, exclusive Android compatibility, and reliance on stable connectivity. TECH-CLASS exhibits significant potential as a scalable attendance verification solution, with next studies aimed at cross-platform compatibility and improved indoor positioning precision
Copyright (c) 2025 Ainul Azila Che Fauzi; Nur Ruzana, Asiah Mat , Noor Ashafiqa, Auni Fauzi https://creativecommons.org/licenses/by-sa/4.0
A DEA CCR APPROACH WITH SUPER-EFFICIENCY RANKING FOR PERFORMANCE EVALUATION OF MALAYSIAN PUBLIC UNIVERSITIES
The efficiency and productivity of a country's higher education system significantly influence its ability to develop and flourish. Furthermore, efficiency becomes a crucial performance metric for universities overall, assisting decision-makers in formulating policies that promote the intended outcomes and prudently allocating resources. There is a lot of pressure on public higher education around the world to perform better and be of higher quality. This study examines the efficiency scores of 20 public universities in Malaysia using the input-oriented CCR model and output-oriented CCR model and also the Super Efficiency model. Three inputs and five outputs are determined to measure the performance of the university. The number of postgraduate students enrolled, the number of undergraduate students enrolled, and the number of academic staff are the inputs, while the number of graduates, the number of graduates working, the number of graduates who choose to further studies, the number of graduates who choose to develop skills, and the number of graduates waiting for work placement are the outputs. The findings show that out of 20 public universities, 13 public universities are efficient with an efficiency score equal to 1 using the input-oriented CCR model and output-oriented CCR model. Meanwhile, the remaining seven public universities showed inefficient score results. UNIMAP got 4.103862 for the Super Efficiency score, which was ranked first out of thirteen efficient public universities in 2023, making it the most efficient public university. By ranking public university, interested parties, such as the higher education sector or university administration, can take steps to enhance and maximize university performance.
Copyright (c) 2025 Norfarziah Adna, Norfarziah Adna https://creativecommons.org/licenses/by-sa/4.0
Clustering Student Internship Placement Using Wards Hierarchical Method
The internship program has been one of the graduation requirements in most higher education institutions. It enables students to undergo a period of training with any organization to acquire skills which cannot be learned in the classroom. The process of acquiring and selecting the internship placement is very crucial to achieving the goals and outcomes of internship program. The place of internship selected by the students is usually situated all over the country. However, the choice of placement made by the student depends on locality of their hometown or a place which can offer high internship job vacancy is not well described. Thus, this study aims to cluster the area of preference by the Mathematics students to do their practical training using Wards Hierarchical Clustering. It was found that the preference area of internship placement chosen by the Mathematics students from the university located in Kelantan state can be clustered into high internship area (Kelantan) followed by medium internship placement area (Selangor, Terengganu, Johor and Perak). Meanwhile, Pulau Pinang, Pahang, Kedah, Kuala Lumpur, Perlis, Putrajaya, Melaka, Negeri Sembilan and Sabah were clustered as low internship placement area. The findings of the research can provide rich insights for the internship management in planning the networking with industry by concentrating on the choice of student’s internship placement.
Copyright (c) 2025 Wan Fairos Wan Yaacob, Wan Faizah Wan Yaacob, Norafefah Binti Mohamad Sobri, Nik Nur Fatin Fatihah Sapri, W. Khairiyah Hulain Wan Ramli https://creativecommons.org/licenses/by-sa/4.0
Development of an Integrated Mobile Application for Food Ordering and Delivery
The Ultimate One-Stop Food Mobile App (QuickBites) aims to revolutionize the food industry within the UiTM Machang campus by providing a user-friendly platform for seamless food ordering and delivery. This mobile application targets students, lecturers, and staff, addressing the challenges of long queues and promoting healthier meal options. Utilizing Android Studio for development and Firebase for real-time data synchronization, the app employs a Rapid Application Development (RAD) approach for swift deployment. The primary objectives of QuickBites include identifying challenges in managing food delivery services, developing an efficient one-stop food center, and evaluating the functionality and usability of the system. Through extensive research and feedback, key issues such as long wait times and the inconvenience of physically visiting food stores were identified. QuickBites addresses these by offering a streamlined interface, real-time order tracking, and integration with various campus food vendors, enhancing the overall food ordering experience. The current version of QuickBites supports only Cash on Delivery (COD) as the payment method. This decision was made to simplify the initial rollout and ensure ease of use for all users. However, this limitation also highlights the need for future enhancements to incorporate diverse payment options to cater to varied user preferences. In conclusion, QuickBites significantly improves the food ordering and delivery experience at UiTM Machang, providing a reliable and efficient tool that meets the needs of its target audience, while also highlighting areas for ongoing enhancement.
Copyright (c) 2025 MAZNIE MANAF, Nurul Ashikin Awang, Marina Ahmad , Noorfadzilah Arifin, Wan Saiful ‘Azzam Wan Ismail https://creativecommons.org/licenses/by-sa/4.0
A Study on the Effects of Social Media Influencer on Consumer Purchase Intention Using Multiple Linear Regression
The rise of social media has transformed how consumers discover, evaluate, and decide to purchase products since nowadays it is often influenced by online personalities known as social media influencers. This study investigates the effects of social media influencers on consumer purchase intention among undergraduate students. As influencer marketing becomes increasingly prominent in digital commerce, this research aims to identify the extent to which trust, credibility, and satisfaction with influencer content impact consumers' buying decisions. The study employs a quantitative, cross-sectional design using a structured questionnaire distributed via online platforms. A sample of 150 students was selected using proportionate stratified random sampling. Descriptive statistics, independent t-tests, Pearson correlation analysis, and multiple linear regression were conducted to analyze the data. The findings reveal that there is not a statistically significant difference in purchase intention based on gender. All three factors, trust, credibility, and satisfaction were significantly correlated with purchase intention. Among these, credibility emerged as the most influential predictor, followed by trust and satisfaction. The regression model explained 78.5% of the variance in purchase intention, indicating strong model fitness. These results suggest that marketers and influencers should prioritize building credibility and trust to enhance campaign effectiveness. The study provides practical insights into tailoring influencer strategies to the preferences of Malaysian university students and contributes to the growing literature on localized digital marketing behavior.
Copyright (c) 2025 NORSHAIEDA ABDULLAH, TENGKU MARDHIAH TENGKU JALAL, SHAFIA IRDINA SHAMSUDDIN https://creativecommons.org/licenses/by-sa/4.0
A Multiple Linear Regression Analysis of Factors Affecting Digital Wallet Adoption among University Students
Digital wallet is an electronic application that offers an easy and safe way of paying for goods and services. The application makes financial transactions without using cash or cards. This study was conducted to determine the factors influencing the adoption of digital wallets by university students based on perceived usefulness, perceived ease of use, and perceived compatibility. Quantitative approach was adopted, and the data were collected through a structured questionnaire distributed to 139 respondents. Multiple linear regression analysis was employed in examining the relationship between the independent variables and the adoption of digital wallets. Results showed that perceived ease of use and perceived compatibility significantly affect digital wallet adoption. These results imply the significance of user friendliness and convenience to make promotion of digital wallet use effectively, proposing that practical convenience and even integration with users’ lifestyle are dominantly outstanding antecedents for adoption among young consumers.
Copyright (c) 2025 Nur Safwati Ibrahim https://creativecommons.org/licenses/by-sa/4.0
The Determinants of Digital Citizenship Skills in Online Safety among Higher Education Students: A Case Study of UiTM Kota Bharu
In today’s digitally connected environment, where students rely extensively on online platforms, strong digital citizenship skills—particularly in online safety—are essential for navigating the digital space responsibly, ethically, and securely. This study examined factors influencing online safety–related digital citizenship skills among undergraduate students at Universiti Teknologi MARA (UiTM) Kota Bharu, focusing on internet attitude, computer self-efficacy, and internet skills. A quantitative cross-sectional design was employed, using data collected from 317 students via an online questionnaire. Stratified random sampling was applied across two faculties—FPP (Faculty of Business and Management) and FSKM (Faculty of Computer and Mathematical Sciences)—to ensure balanced representation. Data were analysed using descriptive statistics, independent t-tests, Pearson correlations, and multiple linear regression. The results showed no significant differences in digital citizenship skills by gender or faculty. However, digital citizenship skills demonstrated strong positive correlations with internet attitude and internet skills, while computer self-efficacy exhibited a weaker yet significant relationship. Regression findings indicated that all three factors significantly predicted digital citizenship skills, with internet attitude emerging as the strongest predictor. These findings underscore the importance of targeted educational initiatives aimed at enhancing digital citizenship, particularly by cultivating positive internet attitudes and strengthening students’ technical competencies.
Copyright (c) 2025 Nor Hazreeni Hamzah https://creativecommons.org/licenses/by-sa/4.0
Determinant of Students’ Spending Behaviour at Uitm Kota Bharu
Students’ spending behaviour refers to the patterns and habits that shape how they manage their financial including expenditures on accommodation, food, entertainment, books, and personal needs. Understanding this behaviour is essential to identify the factors that influence students’ financial decisions and promote responsible money management This study aims to examine the determinants influencing students’ spending behaviour, focusing on five key factors: financial management knowledge, price elasticity, parental income, peer influence, and lifestyle. A total of 207 students participated in this study through stratified random Data were analyzed Pearson’s correlation, and multiple linear regression Pearson’s correlation analysis further reveals significant relationships between students’ spending behaviour and all five examined variables. However, the multiple regression analysis identifies only two factors that are peer influence and lifestyle have significant predictors of students’ spending behaviour. These findings highlight the strong role of social interactions and lifestyle preferences in shaping financial habits, suggesting that financial education initiatives should emphasize the influence of peers and lifestyle choices to enhance students’ financial responsibility.
Copyright (c) 2025 Norafefah Binti Mohamad Sobri, Nur Syaliza Hanim Che Yusof, Nor Azima Ismail, Siti Nurani Zulkfli, Nor fatihah Abd Razak, Mohd Azry Abd Malik https://creativecommons.org/licenses/by-sa/4.0
Modelling Malaysia Production of Logs using Box-Jenkins Model
Comprehending Malaysia’s logs production not only explaining the trend of the Malaysia's GDP. It is also essential for the country as it influences revenue and shapes policies regarding forest resources. Studying the time series of Malaysia logs production is very important for providing comprehensive understanding in making decisions regarding economic development, resource management, and environmental sustainability. Thus, this study aims in determining the best time series model for forecasting the Malaysia logs production by applying the Box-Jenkins model. Based on historical yearly data of Malaysia’s logs production from year 1947 to 2021, in overall, the data series exhibit increasing trend and cyclical patterns. ARIMA(0,2,1) is found to be the best model for forecasting the Malaysia’s logs production where it forecasts values are having decreasing trend.
Copyright (c) 2025 TENGKU MARDHIAH TENGKU JALAL, Norshaieda Abdullah, Muhammad Irfan Haqiem Hairan , Muhammad Wabeel Luqman Shahmiral https://creativecommons.org/licenses/by-sa/4.0
Stability and Prediction of HFMD Dynamics in Malaysia using an SIR Model
Hand, foot, and mouth disease (HFMD) remains a significant public health concern in Asia, with Malaysia and neighbouring countries frequently reporting outbreaks. To better understand its transmission dynamics, this paper applies a Susceptible-Infected-Recovered (SIR) model to HFMD in Malaysia. The analysis focuses on model positivity, equilibrium behaviour, and stability, while the basic reproduction number (R0) is derived using the next-generation method. Two threshold scenarios are considered: when R0<1, the disease-free equilibrium is stable, indicating eventual eradication, whereas when R0>1, the endemic equilibrium is stable, signifying sustained transmission. Numerical simulations support these theoretical results and emphasize the critical role of R0 in shaping outbreak outcomes. A key contribution of this paper is the examination of infection risk variation, showing that higher risks accelerate the shift to endemic persistence, while lower risks extend the stability of the disease-free state. Overall, the findings highlight the importance of threshold dynamics and infection risk in determining HFMD spread. By integrating analytical and numerical approaches, this study offers insights that can inform more effective public health strategies in Malaysia.
Copyright (c) 2025 Zati Iwani Abdul Manaf, Nor Atirah Najwa Che Noor Shan https://creativecommons.org/licenses/by-sa/4.0
TripMate: Smart Travel Assistance Mobile Application
TripMate is a smart travel assistance mobile application that makes the travel planning process smooth and easy. In this application, traveller can book for the interested group tour and rent a car during the trip and both of these services are managed by travel agent. Local buddy service act as the role of local guide that brings traveller in exploring the local culture and cuisine. Each traveller can apply to become a local buddy in order to promote own country’s culture to others. In current market, there are not an application allows traveller to book and compare the group tour price without switching from various in the existing market. These current challenges therefore inspired the creation of TripMate as a solution to the travel booking system in current markets. Using the Waterfall Model as the primary research methodology, TripMate aims to develop an application that enables travellers make bookings easily and integrated the features that can be useful during the trip such as car rental and local buddy functionality. The functional testing such as unit testing and integration testing have been conducted and the non-functional testing such as performance testing is conducted to evaluate the performance of TripMate in real mobile device. Overall, the testing result is passed and indicated an ideal result.
Copyright (c) 2025 Jing Ying Ng, Kavitha Thamadharan https://creativecommons.org/licenses/by-sa/4.0
Bifurcation Analysis of Stage-structured Prey-predator Interactions in Sea Turtle Populations
In this study, a stage-structured prey-predator model is used to describe the dynamics of sea turtles and their marine predators across different life stages. Marine predators primarily target hatchlings, while mature sea turtles can survive independently and immature individuals often rely on external support. This paper employs stability analysis and bifurcation analysis and treating the conversion rate from sea turtle eggs to hatchlings as the bifurcation parameter. Graphical results, including bifurcation diagrams, phase-plane plots, and time series graphs, are produced with XPPAUT, Maple, and MATLAB, respectively. The analysis identifies a transcritical bifurcation point that marks a change in system stability under varying conversion rates. Moreover, the results demonstrate that the conversion rate strongly influences prey-predator dynamics: low rates can cause predator extinction, moderate rates allow coexistence, and high rates increase predation on hatchlings. Overall, the study highlights the ecological importance of hatching rates for maintaining balance and guiding conservation strategies, with particular attention to preventing species extinction.
Copyright (c) 2025 Zati Iwani Abdul Manaf, Muhammad Arif Azhar Khairulriza, Muhammad Syauqi Abdul Ghani, Nur Syasya Iwanie Mohd Arifin https://creativecommons.org/licenses/by-sa/4.0
Neutrosophic Soft Set with Application in Decision Making: A Case Study on Online Food Delivery
The global online food delivery (OFD) market has experienced significant growth, particularly accelerated by the COVID-19 pandemic. This surge is largely attributed to the convenience of ordering meals online and having them delivered directly to consumers’ homes. Additional services offered by OFD platforms have proven essential in supporting social distancing efforts, expanding service accessibility, and minimising the gap between purchase and consumption. In Malaysia, the OFD sector has grown rapidly, presenting vast opportunities for various platforms while simultaneously intensifying market competition. To sustain this growth and adapt to evolving consumer demands, OFD providers must consider multiple strategic dimensions. This study aims to identify the most preferred OFD service among students at Universiti Teknologi MARA (UiTM) Kelantan Branch and to determine the most influential factors affecting their purchasing decisions. The neutrosophic soft set method is employed to analyse expert linguistic evaluations across six key parameters: delivery cost, delivery speed, convenience of payment, web design, marketing techniques, and order fulfillment. The findings reveal that Grab Food is the preferred OFD platform, outperforming Food Panda. Moreover, “convenience of payment” emerged as the most influential parameter driving students’ decisions to use OFD services.
Copyright (c) 2025 Firdawati Mohamed, Nurul Balqis Binti Ramli, Siti Hajar Aisyah Binti Mohamed Saedan https://creativecommons.org/licenses/by-sa/4.0
STUDYMATE: A Centralised Study Note Web Application Enhanced by LLM for Technical Majors
Cognitive overload presents a considerable obstacle for self-directed learners, who are required to manage and assimilate extensive amounts of study materials from many sources. StudyMate, a centralised web-based program, aims to lessen this difficulty by optimising the self-study process. The system incorporates Large Language Models (LLMs) to analyse submitted documents and offer intelligent study support, including summarisation, key point extraction, and flashcard generation, thereby alleviating the cognitive burden of digesting extensive information. StudyMate offers features including organised note management, an intuitive user interface, annotation capabilities, and a comprehensive text editor to enhance organisation, usability, and user engagement. This study concentrates on students in technical disciplines (IT, Computer Science, and Electrical and Electronics Engineering), as StudyMate is designed for self-directed learners, and the creator is well-acquainted with their specific academic requirements and obstacles. The system, developed under the Waterfall model, underwent evaluation via usability testing. LLM-based elements attained an average rating of 4.40 out of 5 for clarity and relevance in study assistance, whereas organisational and note-taking capabilities garnered a satisfaction score of 4.11 out of 5. The findings underscore StudyMate's capacity to alleviate cognitive stress and enhance the learning experience for autonomous learners, especially in technical fields.
Copyright (c) 2025 Chow Ching Huey; Khor Jia Yun https://creativecommons.org/licenses/by-sa/4.0
Deep Learning Algorithms for Skin Condition Classification
Skincare is an essential aspect of personal care, but selecting suitable products remains challenging due to individual variations in skin type and condition. Existing skincare recommendation systems rely on questionnaires, which may lead to inaccurate recommendations. This study explores the application of machine learning algorithms, particularly Convolutional Neural Networks (CNNs), for automated skin analysis and personalised skincare recommendations. By analysing images of users’ skin, the system can classify skin types, detect conditions such as acne or dryness, and suggest suitable products. The study evaluates different deep learning models, including VGG-16, ResNet-50, and MobileNetV2, comparing their accuracy and efficiency. Experimental results indicate that the proposed model achieves high accuracy in classifying skin conditions, demonstrating the potential of machine learning in revolutionising personalised skincare solutions.
Copyright (c) 2025 Ong Yu Chin, Kavitha Thamadharan https://creativecommons.org/licenses/by-sa/4.0
Bibliometric Analysis of Artificial Intelligence Integration in HRIS for Strategic Upskilling
The integration of artificial intelligence (AI) into Human Resource Information Systems (HRIS) has revolutionised workforce management, enabling strategic upskilling and aligning employee capabilities with organisational goals. This study employs a bibliometric analysis to explore the academic landscape of AI integration in HRIS, focusing on its transformative potential in talent acquisition, performance management, and personalised learning. Drawing from a dataset of 535 publications from 2014 to 2024, the analysis highlights key trends, including the growing emphasis on AI-driven training and interdisciplinary research collaborations. Influential authors, institutions, and thematic areas are identified, providing insights into the evolution of this field. Findings reveal that while AI-enabled HRIS enhances operational efficiency and workforce agility, challenges such as ethical considerations, data privacy, and the lack of longitudinal studies persist. This study underscores the need for empirical case studies and cross-disciplinary approaches to address these gaps. By mapping influential research and uncovering emerging themes, this paper contributes to a deeper understanding of AI’s role in HRIS, offering a foundation for advancing both academic inquiry and practical implementation in strategic workforce development.
Copyright (c) 2025 Yudi Kurniawan Budi Susilo, Nurulhuda Noordin, Fariza Hanis Abdul Razak https://creativecommons.org/licenses/by-sa/4.0
AI and Public Governance in Malaysia: A Literature Review on Ethical, Legal, and Operational Challenges
This literature review intends to explore how artificial intelligence (AI) has affected governance in the public sector, focusing on Malaysia with comparison to various global perspectives. AI is increasingly perceived to be a tool for enhancing efficiency in the processes of governance and decision-making, thereby enhancing transparency and accountability. Its adoption, however, is far from problem-free. Issues that have remained in debates are data privacy, biased algorithms, outdated legal frameworks, and the need for more inclusive and transparent AI systems. By comprehending the studies from 2019 to 2024, this review dives into both the opportunities and challenges of AI in governance, examining its ethical and regulatory implications. A review of the several studies in the current literature highlights several trends, points out deficiencies in the methodologies applied, and indicates the directions of further research. This review demonstrates how AI can change the art of governance but also underlines the urgent need for a robust legal framework, rigorous ethical overview, and measures to ensure data protection for citizens.
Copyright (c) 2025 Nik Mohammad Wafiy Azmi, Muhammad Faris Hami Mohd Zahibi , Muhammad Danish Asyraf Tarudin, Nor Fatihah Shahidan https://creativecommons.org/licenses/by-sa/4.0
Development of a Web-Based Application for Cat Hotel and Grooming Management System using the Waterfall Model
This study examined the difficulties faced by Malaysian companies that provide grooming services and cat hotels due to their dependence on manual reservation and data administration records. Inefficiencies, potential data loss, and a higher chance of errors are all consequences of the manual management system. To make it easier for cat owners to book hotel rooms and grooming appointments online, Paw Palace, a web-based cat hotel and grooming services system, was developed. The system was designed based on the Waterfall model of the System Development Life Cycle (SDLC), which includes five stages: 1) requirements gathering; 2) design; 3) implementation; 4) testing; and 5) maintenance. After the system was completed, an evaluation was conducted to assess its usability and efficiency. According to user acceptance testing derived from the System Usability Scale (SUS) evaluation, every module met the test plan objectives.
Copyright (c) 2025 Siti Hasrinafasya Che Hassan, Nurul Athirah Mohd Zukri, Wan Salfarina Wan Husain , Marina Ahmad https://creativecommons.org/licenses/by-sa/4.0
Machine Learning in Precision Medicine: Transforming Personalized Diagnostics and Treatment
Machine learning (ML) has revolutionized the field of precision medicine, providing advanced tools for personalized diagnostics and treatment strategies. This study employs the PRISMA framework to conduct a bibliometric analysis of ML applications in precision medicine, focusing on cancer diagnostics, personalized treatment, and interdisciplinary collaborations. By analyzing 8,793 articles from the Scopus database, this research identifies trends, leading contributors, and gaps in the field. Results highlight the transformative impact of ML, particularly in enhancing early detection and optimizing therapeutic outcomes. However, challenges such as data heterogeneity and ethical concerns persist. The findings underscore the importance of continued innovation and interdisciplinary efforts to overcome these barriers and fully realize the potential of ML in transforming healthcare.
Copyright (c) 2025 Yudi Kurniawan Budi Susilo, Shamima Abdul Rahman, Kapil Amgain https://creativecommons.org/licenses/by-sa/4.0
A New Framework for 3D Point Cloud Reconstruction of Geometric Object from Multi-View Images
This paper proposed a new framework to enhance the 3D point cloud reconstruction from multi-view images. The accurate 3D point cloud is crucial to produce a 3D model SURF ace which can be used in many applications. There were still challenges in the existing approach to reconstructing accurate 3D point clouds as it involves various camera orientations. This paper proposed a simplified experimental setup based on pure camera translation to capture the images from four viewpoints. Geometric object measurement is used as the ground truth data to measure accuracy. Besides, the optical flow feature match method, perspective projection and image transformation were used to reconstruct the 3D point cloud. The result shows that all objects have an average RMSD value of 1.24mm in width and 1.26mm in depth. These values are lower than the previous method based on the images captured using known rotation, indicating higher accuracy. In future, the generated 3D point cloud can be used to create the 3D model SURF ace.
Copyright (c) 2023 Intan Syaherra Ramli, Rahmita Wirza O.K Rahmat, Ng Seng Beng, Hizmawati Madzin, Puteri Suhaiza Sulaiman https://creativecommons.org/licenses/by-sa/4.0
Utilizing the Fuzzy Analytical Hierarchy Process (FAHP) Approach to Identify the Best Online Food Delivery Services
The rapid growth of online food delivery (OFD) services has led to an overwhelming number of options available to consumers. Choosing the best service provider among the multitude of available options has become a complex decision-making process. This study proposes Fuzzy Analytical Hierarchy Process (FAHP) approach to evaluate and rank three popular OFDs: Foodpanda, GrabFood, and OdaMakan, among students at Universiti Teknologi MARA (UiTM) Kelantan Branch, Kota Bharu Campus. Three experts were invited to assess and rate the performance values of criteria and alternatives using a linguistic scale. The evaluation is based on four criteria: service, cost, time, and quality. The fuzzy set theory is utilized to transform the linguistic evaluation statements of experts into criteria weights that are produced by the FAHP. The results demonstrate the effectiveness of the FAHP in selecting the best OFD and that GrabFood is at the first ranking followed by Foodpanda and OdaMakan. Cost is identified as the most important criterion followed by time, service, and quality. The findings of this study can assist OFD providers in understanding the factors that contribute to customer satisfaction and help them to improve their services accordingly.
Copyright (c) 2023 Wan Nurul Husna Wan Nordin, Suziana Aida Othman, Masnira Ramli, Syahirah Aqilah Abdul Rashid, Nurul Najiha Najwa Sukri https://creativecommons.org/licenses/by-sa/4.0
Factors Influencing Mathematics Anxiety Among Undergraduate Students using Regression Model
Mathematics anxiety remains a common issue in education today, impacting students of all ages. This phenomenon has been documented across multiple generations, but its impact on the current generation of students is particularly interesting. This study aims to determine the factors influencing mathematics anxiety among undergraduate students at Universiti Teknologi Mara Kelantan Branch. The study investigated variables such as courses, teacher related factor, spatial abilities, socio-economic factors, and parent factor and evaluated their impact on students’ mathematics anxiety. The study involved the participation of 320 students, who were selected randomly and completed questionnaires using Google Form. The collected data was subjected to analysis using the multiple linear regression method. The findings highlighted that teacher related factor and spatial abilities significantly influenced mathematics anxiety among students, while courses, socio-economic factors, and parent factor played a comparatively lesser role. In addition to expanding our understanding of the mechanisms underlying mathematical anxiety, this research offers insightful information to researchers, parents, educators, and the public. The authors emphasise the importance of educational intervention and awareness strategies as they offer suggestions and recommendations for strategic guidance in managing mathematics anxiety.
Copyright (c) 2024 Norshaieda Abdullah , Amira Zulaikha Mohd Zukki , Che Rosemanita Che Husin, Wan Norhidayah Wan Nawang https://creativecommons.org/licenses/by-sa/4.0
Structural Equation Modelling of Factors Influencing Students’ Perception Towards Academic Performance
Academic performance is a central focus in education, reflecting a student’s ability to understand and apply knowledge across various subjects while shaping their skills and attitudes. This study aimed to examine the relationship between factors (personal, teacher, institution, household) and perception on academic performance. In this study, a cross-sectional design was employed, selecting 183 students from two chosen cluster schools in Kelantan to determine the factors affecting students’ perceptions of academic performance. Data were collected through a set of questionnaires and analysed using structural equation modelling (SEM) with partial least squares (PLS) in SmartPLS software using explanatory factor analysis. This study employed descriptive analyses, Pearson’s correlation coefficient, and a structural equation model approach to comprehensively evaluate both the measurement and structural models. Results revealed a moderate relationship with students’ perceptions of academic performance, whereas other variables such as teacher factor, institution factor, and household factor have a weak relationship. Apart from that, the findings indicate an insignificant relationship between teacher factors and perception of academic performance. Meanwhile, the perception of academic performance is significantly influenced by household, institutional, and personal factors. Consequently, the findings will allow relevant authorities, especially the educational authorities, to enhance academic achievement by addressing the key factors that influence students’ academic achievement in cluster schools.
Copyright (c) 2024 Mohd Noor Azam Nafi, Siti Nurhafizah Mohd Shafie, Nasuhar Ab. Aziz, Siti Nur Atiqah Mohd Shafie https://creativecommons.org/licenses/by-sa/4.0