JOURNAL INFORMATION AND TECHNOLOGY MANAGEMENT (JISTM)

A HUMAN-CENTRIC RESIDENTIAL SAFETY SYSTEM FOR INDEPENDENT ELDERLY INDIVIDUALS

Noor Hafizah Khairul Anuar — 2026-09-07

The number of ageing individuals who live alone increases the necessity of holistic residential safety measures. This research paper portrays the human-centred smart home safety system combining environmental hazards detection, as well as activity monitoring. The system incorporates the use of gas, flame, temperature and humidity sensors, along with (ultrasonic-based) occupancy tracking to check high-risk areas, especially bedding and toilet areas. The core of the solution is an ESP32 microcontroller that allows real-time data collection, local notifications, and IoT-based features through the Blynk and Telegram platforms. To test the performance of the system, a prototype residential model was created, which showed experimental outcomes displaying that the average alert latency was about 1.97 seconds, which means that the system is nearly able to respond to emergencies in real-time. The proposed system can offer a cost-effective, non-invasive, and practical way of improving the safety of the residence by integrating both environmental sensing and time-based analysis of activities. The results prove the practicability of incorporating the multi-sensor monitoring system into the IoT connectivity to ensure the safety of independent living of older citizens.

DIGITAL TRANSFORMATION IN MOSQUE GOVERNANCE: A TECHNOLOGY-ENABLED OUTREACH MODEL FOR ELDERLY ZAKAT ADMINISTRATION IN KEDAH

Noorlailahusna Mohd Yusof — 2026-09-20

The rapid demographic shift towards an ageing society presents significant socio-economic challenges in Malaysia, particularly within rural and semi-urban states such as Kedah. Although local mosques (masjid kariah) serve as important socio-religious hubs, existing mosque-based zakat systems frequently rely on manual, reactive, and fragmented processes. Consequently, vulnerable older persons risk being overlooked, whilst instances of aid duplication persist. Based on a qualitative synthesis of relevant literature and institutional frameworks, this study proposes a conceptual framework titled the Mosque-Led Ecosystem for Zakat Management (MLEZOM) to optimize localized Islamic social finance. Unlike traditional manual and fragmented mosque-based zakat practices, MLEZOM introduces distinct novelty through the systematic integration of digital profiling, youth-assisted community outreach, and multi-tier institutional coordination. The model comprises four core operational pillars: (1) digital profiling and needs assessment, (2) youth-assisted outreach networks, (3) SOP and service delivery development, and (4) impact monitoring and evaluation. By structuring these components into an integrated workflow, the framework aims to reduce the risk of overlooking vulnerable asnaf and improve distribution accuracy. Ultimately, the proposed model illustrates how localized socio-technical governance can strengthen institutional trust, streamline administrative operations, and maximize the social impact of mosque-based financial distribution.

OPTIMIZING CAMPUS CAFETERIA OPERATIONS: DEVELOPMENT AND USABILITY EVALUATION OF THE EATSY MOBILE FOOD ORDERING SYSTEM

Nik Nur’Iffah Nadirah Nik Azman — 2026-09-28

Technological advancement has changed the landscape of the food service industry. People nowadays place their food orders using food service applications. However, university students still need to queue up at the cafeteria to get their food. During peak hours, university students face long lines and significant delays, wasting their valuable time due to inefficient manual order management at the cafeteria. The problems affect students' satisfaction and cafeteria staff productivity. Therefore, this project aimed to address these challenges by designing a user-friendly Android mobile application food ordering system, Eatsy in the context of cafeteria at the University Teknologi MARA (UiTM) Machang Campus. The application has been developed using Rapid Application Development (RAD) methodology which involves Requirements Planning, User Design, Construction and Cutover phases to improve the dining service experience. Eatsy allows students to order food at cafeteria wherever they are, and they could track the status of their orders in real-time. This application also helps cafeteria staff managing order effectively. At the Cutover phase, a preliminary usability test with the System Usability Scale (SUS) was performed with a purposeful sample of users. The result of the evaluation showed an average of SUS score of 91.25 which is considered as very high user acceptance and system usability. Overall, the implementation of Eatsy proves to be a viable digital transformation strategy, aimed at minimizing operational delays, optimizing the service offering and enriching the dining experience at the Campus. Future research directions involve utilization of intelligent recommendation system and extension of architecture to support sustainable operation of multi-cafeteria systems.

DESIGNING A USER-CENTRIC MOBILE INTERVENTION FOR FOOD WASTE REDUCTION IN MALAYSIAN URBAN HOUSEHOLD: A DESIGN THINKING APPROACH

Hui Lin Wong — 2026-09-15

In Malaysia, generation of household food waste is more serious than the food waste generated from other industries or sectors. Urban households generally generate more food wastes although high level of awareness on the impact of environmental sustainability. They aware the issue and understand the consequences, but less effective action has been taken to manage or reduce the food waste, and therefore, create a say-do-gap. This study aimed to explore the perspectives, needs, challenges, and motivations of food waste reduction in urban household Malaysia using design thinking approach. Semi-structured interview and site-observation were conducted in empathy stage. A total of 11 participants were targeted in the interview session. The 11 participants were categorized into five distinct user personas, including Health-Conscious Individual Cook, The Cultural Compliance Professional, The Green-Minded Urban Renter, The Guilty Minimalist Professional, and The Practical Disposer. Study revealed the reasons of forgetfulness, over-purchasing, and improper food storage contributed to the generation of food waste. To address the challenges, the “GLANCE” digital app for food planning and inventory tracking was designed, introduced, and tested by four users in prototype and test stages. Online survey form was distributed to the participants, and the testing results showed the participants were strongly agreed the user-friendliness and practicability of the app. Overall, the study was designed as an exploratory pilot to establish proof of concept, the app can further improve for long-term user engagement.

AI-DRIVEN LEARNING FOR IMC413: ENHANCING MASTERY THROUGH ASKME247

Ahmad Zam Hariro Samsudin — 2026-09-28

This study assesses AskMe247's instructional viability and pedagogical efficacy, a course-specific AI-driven learning assistant engineered to support higher education students in mastering IMC413 Information Storage and Retrieval. The course presents learning challenges due to its abstract theoretical constructs and dense technical terminology, such as search algorithms, metadata indexing, and retrieval models. Employing a mixed-methods design, empirical data were gathered from 40 respondent of IMC413 students, who had been selected across two distinct academic cohorts using purposive sampling. Quantitative survey metrics evaluating ease of use, conceptual mastery, efficiency, and engagement were combined with qualitative open-ended responses and continuous system usage logs collected over one semester. Results reveal that AskMe247 significantly enhanced student’s self-reported confidence and conceptual comprehension, with over 80% of respondents reporting improved clarity on complex topics previously unaddressed in live lectures due to hesitation. Students described AskMe247 as easing anxiety, acting like a confidence enhancer and serving as a constant personal tutor, while usage logs indicated peak engagement during exam preparation weeks. additionally, the platform showed initial utility in streamlining routine inquiry resolution, thereby lowering repetitive instructional workload. The implication of this research is the research helps educators implement AI tools in classroom settings and outlines simple safety measure for source attribution and fair content use. Instead of relying on generic conversational AI, AskMe247 shows how specialized, adaptive systems can be embedded into technical courses to bridge classroom instruction with self-directed study. The implications of this study show how educators can incorporate domain-tailored AI tools into classroom environments while keeping simple safeguards for source attribution and fair content use. Instead of depending on broad, general-purpose conversational models, AskMe247 demonstrates how adaptive, course-specific AI can connect classroom instruction with self-directed study, encouraging deeper learning and supporting technical curricula.

USER-CENTRIC INVESTIGATION ON ICT ADOPTION AMONG RURAL FARMERS IN KELANTAN

Zuriani Ahmad Zukarnain — 2026-09-03

Agriculture is a major economic activity in Kelantan, where many rural communities rely on small-scale farming for their income. However, productivity remain low due to several factors such as limited mechanization and access to information. Nowadays Information and Communication Technology (ICT) play a significant role in improving agricultural activity including farm management, market access, and decision-making. Despite national initiatives to improve digital inclusion in agriculture such as the Digital Economy Blueprint (MyDIGITAL) and the National Agrofood Policy 2021–2030 (NAP 2.0), there are still a lot of challenges in ICT adoption among rural farmers in Kelantan. This study aimed to assess the reliability and suitability of a questionnaire designed to measure farmers’ perceptions toward ICT adoption and to identify preliminary patterns of awareness, attitudes, and challenges. A quantitative approach was employed using a structured questionnaire comprising 24 items with six constructs including importance, ease of use, knowledge, equipment, cost, and attitude. Data collected from 30 rural farmers were analyzed and presented using descriptive statistics. All constructs demonstrated acceptable reliability, with Cronbach alpha values ranging from 0.76 to 0.84. The findings confirm that the instrument is reliable and suitable for large-scale use while emphasizing the need for improved digital infrastructure and farmer training.

MUSLIMAH SMART TRACKER: ANALISIS KEPERLUAN APLIKASI PINTAR BAGI IDENTIFIKASI DARAH WANITA BERASASKAN MAZHAB SYAFI‘I

Nur Fatin Nabilah Shahrom — 2026-09-20

Perbahasan fiqh berkaitan darah wanita seperti haid, nifas dan istihadhah merupakan aspek penting dalam hukum ibadah kerana ia berkait rapat dengan kesahan amalan seperti solat dan puasa. Walaupun hukum berkaitan darah wanita telah dihuraikan secara terperinci dalam literatur fiqh, khususnya dalam mazhab Syafi‘i, wanita Muslim pada hari ini masih berhadapan dengan kekeliruan dalam menentukan jenis darah dan implikasi hukumnya dalam situasi tertentu. Seiring dengan perkembangan teknologi digital, penggunaan aplikasi mudah alih dilihat berpotensi menjadi medium sokongan dalam membantu wanita Muslim memahami dan mengurus isu fiqh darah wanita secara lebih sistematik. Justeru, kajian ini dijalankan untuk menganalisis tahap pengetahuan, kefahaman dan keyakinan wanita Muslim terhadap fiqh darah wanita serta menilai keperluan pembangunan aplikasi pintar bagi identifikasi darah wanita berasaskan mazhab Syafi‘i. Kajian ini menggunakan pendekatan kuantitatif melalui kaedah tinjauan soal selidik yang melibatkan 411 orang responden wanita Muslim daripada institusi pengajian tinggi. Data dianalisis menggunakan statistik deskriptif bagi mengenal pasti tahap pengetahuan, kefahaman situasi, keyakinan diri serta keperluan responden terhadap aplikasi digital. Hasil kajian menunjukkan bahawa tahap pengetahuan responden berkaitan darah wanita berada pada tahap tinggi dengan skor min 4.13, diikuti tahap kefahaman situasi (min = 3.79) dan keyakinan diri (min = 3.69). Walau bagaimanapun, responden masih menunjukkan kekeliruan dalam beberapa situasi praktikal seperti membezakan antara haid dan istihadhah serta menangani kitaran haid tidak menentu. Kajian ini juga mendapati bahawa responden menunjukkan tahap kesediaan yang tinggi untuk menggunakan aplikasi digital berasaskan hukum syariah (min = 3.68), manakala spesifikasi keperluan aplikasi berada pada tahap sangat tinggi (min = 4.36), khususnya dari segi panduan hukum mazhab Syafi‘i, fungsi pengiraan automatik dan reka bentuk mesra pengguna. Sebagai implikasi, kajian ini membuktikan bahawa pembangunan aplikasi pintar identifikasi darah wanita berasaskan mazhab Syafi‘i berpotensi membantu meningkatkan kefahaman praktikal fiqh wanita serta memudahkan akses kepada panduan hukum yang sahih dalam era digital.

Fiqh discussions related to women’s blood such as menstruation (hayd), postnatal bleeding (nifas), and irregular bleeding (istihadah) constitute an important aspect of Islamic jurisprudence because they are closely related to the validity of acts of worship such as prayer and fasting. Although rulings concerning women’s blood have been extensively discussed in classical and contemporary fiqh literature, particularly within the Shafi’i school of thought, Muslim women today still face confusion in determining the type of blood and its legal implications in certain situations. In line with the development of digital technology, mobile applications are seen to have the potential to serve as supportive tools in assisting Muslim women to understand and manage issues related to the fiqh of women’s blood in a more systematic manner. Therefore, this study was conducted to analyse the level of knowledge, understanding, and confidence of Muslim women regarding the fiqh of women’s blood, as well as to evaluate the need for the development of a smart application for identifying women’s blood based on the Shafi’i school of thought. This study employed a quantitative approach using a survey questionnaire involving 411 Muslim female respondents from higher education institutions. The data were analysed using descriptive statistics to identify respondents’ levels of knowledge, situational understanding, self-confidence, and their need for a digital application. The findings indicate that the respondents’ level of knowledge regarding women’s blood is high, with a mean score of 4.13, followed by situational understanding (mean = 3.79) and self-confidence (mean = 3.69). Nevertheless, respondents still experience confusion in several practical situations, such as distinguishing between menstruation and irregular bleeding, as well as dealing with irregular menstrual cycles. The study also found that respondents demonstrate a high level of readiness to use a digital application based on Islamic legal rulings (mean = 3.68), while the application requirement specifications were rated at a very high level (mean = 4.36), particularly in terms of Shafi’i legal guidance, automatic calculation functions, and user-friendly design. As an implication, this study demonstrates that the development of a smart application for identifying women’s blood based on the Shafi’i school of thought has the potential to enhance practical understanding of women’s fiqh and facilitate access to authentic legal guidance in the digital era.

CONCEPTUALIZING AND VALIDATING SOCIO-ALGORITHMIC AI LITERACY (SAILS) AMONG MALAYSIAN UNIVERSITY STUDENTS: A PROPOSED FRAMEWORK

Zuraidah Arif — 2026-09-28

The current measures of AI literacy tools assess technical skills, mechanics of prompt engineering, and basic ethical considerations but do not account for socio-algorithmic vulnerability or increased susceptibility to cognitive persuasion, uncritical trust, and unintended privacy breaches due to conversational interface persuasion tactics. Drawing on theoretical constructs such as CASA (Computers Are Social Actors), Dual Process Theory, and Information Literacy. Socio-Algorithmic AI Literacy (SAIL) is defined as the psychological and behavioral ability of an individual to be aware of, assess, and reject mindless social scripts triggered through the interaction of humans with human-like AI. This study provides a theoretical framework for the development and validation of Socio-Algorithmic AI Literacy Scale (SAILS) for HEI students from Malaysia. By advancing AI literacy beyond mere operational knowledge towards identification and management of socio-algorithmic risks, SAILS is able to provide a reliable instrument for assessing the readiness of students in this regard at the Ministry of Higher Education Malaysia, university senates, and academic libraries.

TRACING THE ISLAMIC INTELLECTUAL LEGACY IN THE CONCEPTUAL FOUNDATIONS OF GENERATIVE ARTIFICIAL INTELLIGENCE

Wan Rusydiah Salehudin — 2026-09-10

The rapid development of Generative Artificial Intelligence (GenAI) has transformed the global technology landscape through the development of Large Language Models (LLMs), Deep Learning (DL) and multimodal content generation systems. Nevertheless, mainstream historiography Artificial Intelligence (AI) often situates its development within the modern Western tradition, while there are significant contributions from Islamic civilization remain underappreciated. Therefore, this study aims to examine the conceptual relationship between Islamic intellectual traditions and the intellectual foundations of GenAI through a historical and epistemological analysis. Specifically, this study seeks to (i) identify major concepts within Islamic intellectual heritage that demonstrate conceptual relevance to GenAI, (ii) analyse their significance within the broader evolution of computational thought, and (iii) discuss their implications for contemporary debates concerning AI ethics, governance and human-centred technological development. This study adopts a qualitative historical approach through a literature analysis of scholarly works related to the history of science, Islamic philosophy and GenAI. This article argues that Islamic intellectual traditions have indirectly contributed to the conceptual foundations of GenAI through the development of formal logical reasoning systems, algebraic methodologies and algorithms, as well as language and knowledge analysis structures. Although Islamic scholars did not develop GenAI in its modern form, their frameworks of thought formed part of the epistemological and technical foundations that ultimately influenced the development of modern computing and GenAI. This study also asserts that Islamic traditions offer important ethical and epistemological dimensions in understanding the limitations of AI as well as the importance of human oversight in future technological development.

DIGITAL TOOLS AND EMPLOYEE WELL-BEING IN THE MODERN WORKFORCE: A THEMATIC REVIEW

Norhafizah Abdul Halim — 2026-09-28

The increasing use of digital technologies has changed how work is organized, communicated, and experienced. Although digital tools can support employee well-being, their use may also create new sources of psychological strain. This review examines how digital tools shape employee well-being by synthesizing the literature around three interrelated themes: digital tools as resources for well-being, digital tools as sources of psychological strain, and the management of well-being in an AI-enabled workplace. The review draws on literature retrieved through Scopus and examined using Scopus AI as an analytical support tool as of 25 September 2025. The review process combined database searching, Scopus AI-generated summaries and concept mapping, and thematic interpretation of relevant studies. The synthesis indicates that digital tools can strengthen communication, collaboration, flexibility, engagement, and access to work resources. At the same time, excessive connectivity, technology-related demands, blurred work–life boundaries, and insufficient digital support can contribute to technostress and reduced well-being. The literature further indicates that artificial intelligence introduces a more complex set of opportunities and concerns because automation, monitoring, and decision-support systems can alter employee autonomy, workload, privacy, and perceptions of control. Overall, employee well-being appears to depend less on the presence of technology itself than on how digital tools are designed, introduced, and supported within organizations. The review highlights the importance of human-centred implementation, appropriate organizational support, digital capability development, and clear boundaries around technology use.

DIGITAL LITERACY AND LEARNING ADAPTABILITY AMONG UNIVERSITY STUDENTS IN CHINA: A CONCEPTUAL REVIEW IN THE ERA OF DIGITAL EDUCATION TRANSFORMATION

Hui Zhao — 2026-09-03

The rapid advancement of digital technologies has fundamentally transformed higher education, reshaping how students acquire knowledge, interact with learning resources, and engage in academic activities. As universities increasingly adopt technology-enhanced learning environments, students are expected to develop not only digital competencies but also the capacity to adapt effectively to continuous pedagogical and technological changes. Consequently, digital literacy and learning adaptability have emerged as two essential competencies for success in contemporary higher education. This conceptual paper examines the relationship between digital literacy and learning adaptability among university students in China. Drawing on the Digital Competence Framework for Citizens (DigComp 2.2), digital literacy is conceptualised as a multidimensional construct comprising five core domains: information and data literacy, digital communication and collaboration, digital content creation, digital safety, and digital problem-solving. Learning adaptability is defined as students’ ability to adjust their cognitive, behavioural, emotional, motivational, and social responses to evolving learning environments and academic demands. The study employs a Narrative Literature Review (NLR) approach to synthesise and critically interpret existing literature related to both constructs. The thematic synthesis indicates that digital literacy serves as a foundational enabler of learning adaptability by enhancing students’ ability to navigate digital environments, engage in self-directed learning, and respond effectively to technological and pedagogical changes. The review also identifies significant research gaps, particularly within the context of Chinese higher education, where empirical evidence on the relationship between digital literacy and learning adaptability remains limited. Overall, this paper contributes to the growing discourse on educational digital transformation by providing a conceptual framework that integrates digital competencies with adaptive learning capabilities. The proposed framework offers a theoretical foundation for future empirical research and highlights the importance of fostering both competencies to enhance student success and lifelong learning readiness in an increasingly digital educational landscape.

COMPARATIVE ANALYSIS OF 2D AND 3D LIDAR-BASED OBJECT DETECTION FOR MARITIME NAVIGATION

Aiman Norazaruddin — 2026-09-17

Maritime navigation safety relies on the timely and accurate detection of obstacles such as vessels, buoys, and floating debris. Conventional sensing technologies, including radar and optical cameras, are limited by low resolution, reduced performance in adverse weather, and susceptibility to sea clutter. Light Detection and Ranging (LiDAR), with its high-resolution three-dimensional sensing capability, offers a promising alternative; however, its application in maritime environments remains relatively underexplored compared to autonomous road vehicles. This study presents a LiDAR-based object detection framework for maritime navigation and evaluates the performance of two-dimensional (2D) and three-dimensional (3D) detection approaches using a calibration/projection-based LiDAR-camera fusion scheme, in which 2D detections are associated with LiDAR points to obtain 3D object localisation. A Velodyne mechanical LiDAR and a ZED stereo camera were mounted on a marine vessel operating in the waters of Klang, Malaysia. Training data were obtained from the Singapore Maritime Dataset, the SeaShips Dataset, and a custom-collected maritime dataset annotated using Roboflow for 2D images and labelCloud for 3D point clouds. A YOLOv8-based model was developed for 2D object detection, while a parallel pipeline generated point clouds from depth imagery for 3D bounding-box estimation. Performance was evaluated using precision, recall, F1-score, Intersection-over-Union (IoU), and, for the 2D pipeline, mean Average Precision (mAP50 and mAP50-95). The 2D detection model achieved strong performance, with a precision of 0.94, recall between 0.84 and 0.86, and an F1-score of approximately 0.89. In contrast, the 3D detection pipeline achieved precision, recall, and F1-score of approximately 0.25 each, a gap attributed jointly to the limited availability of annotated 3D maritime data and to the geometric, non-learned nature of the 3D bounding-box generation step, which takes the axis-aligned extent of the associated LiDAR/depth point cloud without a mechanism to reject noise or clutter points. Comparative analysis also showed that the Velodyne LiDAR produced denser and more accurate point clouds than the ZED stereo camera, particularly for distant objects where stereo depth estimation degraded. The proposed framework demonstrates the effectiveness of LiDAR-camera fusion for maritime 2D object detection while highlighting current challenges in 3D maritime perception. It provides an end-to-end baseline for future sensor-fusion research supporting safer autonomous and assisted maritime navigation.

CYBERSECURITY AWARENESS IN EDUCATIONAL INSTITUTIONS: A CRITICAL SOCIO-TECHNICAL REVIEW OF BEHAVIOURAL, PEDAGOGICAL AND GOVERNANCE INTERVENTIONS

Nor Hafizah Abdul Razak — 2026-09-28

The increasing reliance on cloud services, learning management systems and connected devices has expended opportunities for teaching and learning within educational institutions. However, it also causes the risk of phishing, ransomware, data misuse and social engineering. So, this critical literature review examines cybersecurity awareness across primary, secondary and higher education from a socio-technical perspective. A structured search of academic research databases including Scopus, Web of Science, IEEE Xplore and ERIC, identified peer-reviewed studies published between 2021 and 2026. 15 studies have retained for thematic synthesis after duplicate elimination and staged screening. The analysis integrates Protection Motivation Theory (PMT) and Socio-Technical Systems (STS) theory to capture both individual and contextual influences on secure behaviour. PMT was used to interpret individual threat perception, coping appraisal and self-efficacy, while STS theory to examine how institutional and technological conditions influence secure behaviour. A persistent gap between recognizing cybersecurity risks and knowing how to respond to the risk has been highlighted from the synthesis. Although, interactive and gamified interventions generally report improvements in short-term knowledge or awareness, the reviewed studies show that this evidence of sustained behavioural change remains limited. The reviewed studies also indicate that teacher capability, governance arrangements and institutional readiness influence whether cybersecurity knowledge is translated into practice. Across the literature, continuous assessment and role-specific training are presented more consistently as components of sustained cybersecurity practice than isolated awareness activities. These findings also question the adequacy of the “human firewall” metaphor, which places considerable responsibility on individual users while giving less attention to system design, governance and resource constraints. Cybersecurity awareness is therefore better understood in this review as an outcome of interactions among threat appraisal, self-efficacy, institutional support and secure system design.

ADOPTION OF DRONE TECHNOLOGY: A PRELIMINARY STUDY AMONG RICE FARMERS IN KADA, KELANTAN

Nor Diana Mohd Idris — 2026-09-10

Despite increasing government support for precision agriculture, empirical evidence on the determinants of drone technology among Malaysian paddy farmers remains limited. This preliminary study addresses this gap by examines the early-stage drivers of drone technology adoption among paddy farmers in Malaysia's Kemubu Agricultural Development Authority (KADA) region. Drawing on the Unified Theory of Acceptance and Use of Technology (UTAUT), the study investigates the role of performance expectancy and social influence in shaping adoption intention. A quantitative survey involving 50 systematically selected farmers were analysed using descriptive statistics, Pearson correlation, and chi-square tests. As a pilot study, the research aimed to evaluate the feasibility of the research instrument and generate preliminary evidence for a larger empirical investigation. Results indicate that social influence demonstrated a stronger positive association with adoption intention than performance expectancy (r = 0.57, p < 0.001). Younger farmers (<40 years) and those with larger farm sizes (>5 acres) reported significantly higher adoption intention, suggesting demographic disparities in uptake. This study extends the application of UTAUT to precision agriculture by providing preliminary evidence from smallholder paddy farmers in Malaysia, a context that remains underexplored in the technology adoption literature. The findings suggest that agricultural extension programmes should leverage peer influence and demonstration farms to accelerate drone adoption, particularly among older farmers and those operating smaller farms. This study offers important groundwork for refining Malaysia’s agricultural modernisation strategies under the National Agro-Food Policy (2021-2030).

THE EVOLUTION OF ARTIFICIAL INTELLIGENCE LITERACY RESEARCH: A BIBLIOMETRIC ANALYSIS

Nor Famiza Tarsik — 2026-09-20

The rapid adoption of artificial intelligence and growing concerns regarding workplace disruption and misinformation, traditional digital literacy frameworks lack updated, systematic mapping to account for the disruptions brought by generative AI. To address this gap, this study identify annual research trends, identifies dominant topics, and evaluates the intellectual structure of AI literacy literature published between 2020 and 2025. Literature was retrieved from the Scopus database following PRISMA systematic screening guidelines and analyzed using VOSviewer for science mapping, Harzing’s Publish or Perish for citation metrics, and Microsoft Excel. A final dataset of 443 records was selected for bibliometric analysis. The analysis reveals an exponential growth in scholarly output, peaking in 2025 with 292 documents (65.91%). The United States (85 publications) and China (80 publications) are the leading research contributors, S.C. Kong is identified as the most prolific author (17 publications), and Computers and Education: Artificial Intelligence serves as the top publication source (25 publications). Analysis also demonstrates a central focus on educational technology and digital competency, with rapidly emerging themes including prompt engineering, academic integrity, large language models, AI ethics and teacher education. This study contributes to the literature by providing a longitudinal evaluation of the post-ChatGPT AI literacy landscape, offering an empirical foundation to inform future policy development and responsible AI integration frameworks.

RESEARCH LANDSCAPE OF SUPPLY CHAIN RISKS IN CONSTRUCTION: A BIBLIOMETRIC REVIEW

Muhamad Norsyafiq Muhamad Nazri — 2026-09-03

The increasing complexity of global construction activities has intensified exposure to supply chain disruptions, creating significant challenges related to procurement, logistics, infrastructure vulnerability, and project sustainability. Despite the growing importance of supply chain risk management in the construction industry, existing studies remain fragmented, with limited understanding of the intellectual structure, research evolution, and emerging thematic trends within this domain. Therefore, this study aims to systematically analyse the research landscape of supply chain risks in the construction industry through a comprehensive bibliometric approach. Data were collected from the Scopus database using an advanced search strategy based on three primary keyword groups: supply chain, risk, and construction industry. Following the screening and refinement process, a total of 76 relevant publications were selected for analysis. The collected bibliographic data were subsequently analysed using the Scopus Analyzer to evaluate publication trends, citation structures, leading countries, influential articles, and source titles. To improve data consistency and reliability, OpenRefine was utilized for data cleaning and harmonization, while VOSviewer was employed to construct visualization networks for keyword co-occurrence and thematic mapping. The findings reveal a significant increase in publication output after 2019, indicating growing scholarly attention toward construction supply chain resilience, infrastructure vulnerability, and sustainability-related risks. The United States, China, and the United Kingdom emerged as the leading contributors to the field, while keyword analysis identified “supply chain management,” “critical infrastructure,” and “vulnerability” as dominant research themes. The study contributes to the body of knowledge by providing a structured overview of the research domain, identifying emerging research directions, and offering valuable insights for researchers and industry practitioners seeking to strengthen supply chain resilience and risk management strategies in the construction sector.

MIXED REALITY (MR) MODEL BASED ON VISUAL INTERACTION (VI) DESIGN PRINCIPLES FOR DEAF LEARNERS: A SYSTEMATIC LITERATURE REVIEW (SLR)

Ermiera Shafika Mokhtar — 2026-09-15

Although Mixed Reality (MR) technologies have increasingly been explored to support Deaf education, existing studies primarily emphasize technological capabilities rather than the visual interaction requirements and cognitive needs of Deaf learners. This study presents a systematic literature review (SLR), following the PRISMA guidelines, to examine MR applications developed for Deaf individuals between 2015 and 2025. Five academic databases were searched using predefined inclusion and exclusion criteria. Eleven MR applications for Deaf individuals were identified, of which six focused specifically on educational settings and were further analysed to examine their features, interaction approaches, and design limitations. The findings indicate that while existing applications incorporate advanced features such as 3D avatars, gesture recognition, and gamified interaction, none systematically integrates Visual Interaction (VI) design principles to support clarity, consistency, accessibility, and cognitive usability. Furthermore, no MR application was specifically developed for Malaysian Deaf learners. Based on these findings, this paper proposes the Mixed Reality–Visual Interaction Design for Deaf Learners (MRVI-DL), a design framework that integrates MR capabilities with VI principles to support the development of accessible and cognitively appropriate learning environments for Deaf learners.

DISCRETIZING BINARY VARIABLES FROM CONTINUOUS VARIABLES FOR SIMULATION DATA GENERATION: A CRITICAL LITERATURE REVIEW

Kartini Kasim — 2026-09-28

Generating simulation datasets with both continuous and categorical variables is essential for evaluation of statistical methods involving mixed variables. Continuous variables can be generated directly from specified distribution, however, generating categorical variables requires procedures, as they cannot be generated directly in the same manner as continuous variables. Several reviews have addressed general data discretization or categorical encoding as procedures for generating categorical variables, but there are limited studies synthesised continuous-to-binary discretization methods for simulation data generation. Therefore, this review aims to synthesise the literature on continuous-to-binary discretization methods for simulation data generation, comparing their strengths, limitations, and suitability across simulation contexts. This literature review was searching using Scopus AI with no restriction on publication year, in which the searching completed in August 2026 yielded 18 peer-reviewed journal articles retained as representative of the major methodological approaches identified. Four methodological themes were identified which are threshold-based discretization, latent-variable and probabilistic modelling, dependence-preserving simulation frameworks, and considerations relating to threshold selection, information loss, and model compatibility. Threshold-based methods are simple and efficient but prone to information loss and biased estimation when thresholds are poorly justified, whereas latent-variable, Gaussian copula, and power-polynomial approaches better preserve dependence structures at the cost of stronger assumptions and greater computational complexity. This review offers a useful methodological reference for selecting discretization methods suited to specific simulation objectives, while identifying limitations and priorities for future research.

STRUCTURE-BASED VALIDATION OF REINFORCEMENT-LEARNING-GENERATED JAK2 TYPE II INHIBITOR CANDIDATES: MOLECULAR DOCKING RESOLVES THE 1D REWARD-HACKING ARTIFACTS OF SINGLE-OBJECTIVE OPTIMIZATION

Yang Xuelan — 2026-09-07

Reinforcement learning (RL) is proving to be a powerful way to tackle generative molecular design. Optimizing molecules using 1D surrogate reward functions, however, is frequently not sufficient to include the biophysical constraints that are necessary for successful drug discovery. Heuristic reward hacking is a problem with existing RL algorithms, which when fed with generated molecules can maximize the heuristic reward, but not produce a meaningful increase in pharmacological activity. This problem is addressed by Janus Kinase 2 (JAK2) Type II inhibitors which represent a challenging standard to meet in three-dimensional structure. We demonstrate that the same 1D surrogate can be used in two ways which are essentially different. Without any constraints, the unconstrained optimization using REINFORCE will lead to a “fragment trap”, which means molecules with low MW and lower than normal “drug-likeness” scores. Constrained optimization, on the other hand, with Proximal Policy Optimization (PPO) leads to molecules that are bigger and more hydrophobic than they need to be, taking advantage of the biases that are in the favor of molecular size and hydrophobicity. Both strategies do not result in the moderate complexity chemotypes essential for an effective JAK2 Type II inhibitor. Therefore, we propose as a orthogonal unsupervised validation step three-dimensional molecular docking as a structure-based surrogate independent of the surrogate reward. Docking re-centers molecular selection by giving preference to candidates in an intermediate molecular weight range (around 470-550 Da) typical of the deep DFG-out allosteric pocket, and systematically down-ranking undersized and oversized molecules. Empirically calculated docking scores are prone to bias based on the size and lipophilicity of the ligands so score differences should be taken with a pinch of salt and the docking is used as a confirmatory filter rather than an absolute affinity oracle. The results in this study show that the validation of molecular 3D structures should be added as another alignment tool in the generative molecular design process, and that the integration of multiple objectives in drug discovery with physically informed knowledge is desirable.

KERANGKA HIBRID ZAKAT-WAKAF BAGI MELESTARIKAN KETAHANAN EKONOMI ASNAF YANG MAMPAN

Surita Hartini Mat Hassan — 2026-09-20

Kemiskinan multidimensi merupakan cabaran utama sosioekonomi yang tidak dapat diselesaikan secara optimum melalui instrumen bantuan saraan jangka pendek semata-mata. Kajian konseptual ini bertujuan meneroka potensi pembinaan kerangka hibrid yang mengintegrasikan fungsi zakat dan wakaf bagi membina ketahanan ekonomi asnaf yang mampan di Malaysia. Melalui kajian konseptual berasaskan analisis dokumen dan sorotan literatur bersistematik, kajian ini menganalisis peranan strategik kedua-dua instrumen kewangan sosial Islam tersebut. Hasil kajian mencadangkan satu kerangka konseptual empat fasa iaitu Penyelamatan Ekonomi, Pemulihan Ekonomi, Pengukuhan Ekonomi dan Ketahanan Ekonomi. Sinergi ini menggunakan kelebihan fungsian zakat sebagai penggerak modal insan dan operasi, manakala wakaf menyediakan aset fizikal dan prasarana kelestarian. Aspek tadbir urus yang telus melalui pengasingan akaun yang jelas (ring-fencing) dan audit Syariah berkala dicadangkan sebagai tonggak pematuhan bagi meningkatkan potensi impak pembangunan asnaf. Kajian ini memberikan implikasi dasar penting bagi institusi zakat dan wakaf dalam merangka model agihan yang lebih berdaya tahan dan lestari.

Multidimensional poverty represents a major socioeconomic challenge that cannot be optimally addressed solely through short-term subsistence assistance. This conceptual study aims to explore the potential for developing a hybrid framework that integrates the functions of zakat and waqf to enhance the livelihood security and build the sustainable economic resilience of asnaf in Malaysia. Employing a qualitative design based on document analysis and a systematic literature review, this study examines the strategic roles of these two Islamic social finance instruments. The findings propose a four-phase conceptual framework comprising Economic Rescue, Economic Recovery, Economic Strengthening, and Economic Resilience. This synergy leverages the functional advantages of zakat as a catalyst for human capital development and operational support, while waqf provides physical assets and sustainable infrastructure. Transparent governance mechanisms through clear account segregation (ring-fencing) and periodic Shariah audits are proposed as key compliance pillars to maximise the developmental impact on asnaf. This study offers important policy implications for zakat and waqf institutions in designing a more resilient and sustainable distribution model.

POINT CLOUD PROCESSING ON 3D LIDAR DATA FOR UNMANNED SURFACE VEHICLES NAVIGATION IN MARINE ENVIRONMENTS

Aiman Norazaruddin — 2026-09-15

Unmanned Surface Vehicles (USVs) require reliable autonomous navigation systems in dynamic maritime environments. LiDAR sensors, while effective for obstacle detection, are susceptible to noise and distortion from wave oscillations and water surface absorption, generating false positives and negatives in point cloud data. Most existing preprocessing-clustering evaluations are confined to terrestrial or simulated settings, with limited benchmarking under real maritime conditions marked by wave-induced motion, surface reflections, and sparse returns. This study addresses that gap through one of the first systematic evaluations of preprocessing-clustering combinations using real harbour LiDAR data collected under genuine environmental disturbance. A Velodyne HDL-32E LiDAR sensor was deployed at Klang Harbour, Malaysia, to collect real-world point cloud datasets. Three preprocessing techniques — Voxel Grid Downsampling, Statistical Outlier Removal (SOR), and Radius Outlier Removal (ROR) — were evaluated with two clustering algorithms chosen for their contrasting noise-handling strategies: Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Euclidean Cluster Extraction (ECE). Performance was assessed using precision and accuracy against manually annotated ground truth. DBSCAN combined with SOR achieved the highest performance, with peak accuracy of 57% (ε = 1.0 m) and peak precision of 62% (ε = 2.0 m), as SOR removes wave-induced outliers while preserving obstacle geometry, enabling DBSCAN's density criterion to isolate genuine clusters more reliably. ROR consistently degraded performance by over-removing genuine sparse returns, while ECE underperformed across all configurations due to its lack of native noise handling. The overall pipeline reached approximately 60% accuracy, a modest ceiling reflecting persistent wave motion, surface reflections, sparse long-range returns, and moving vessels that geometry-based clustering alone cannot resolve. This study contributes a methodological benchmark for preprocessing-clustering pipeline selection in maritime LiDAR processing, and practical guidance for selecting efficient, noise-robust configurations for real-time USV obstacle detection. Future work should incorporate model-based object detection and multi-sensor fusion to improve classification capability and system reliability.

LEADERSHIP COMMUNICATION IN DIGITAL AND AI-ENABLED WORKPLACES: A SCOPING REVIEW

Norhafiza Hashim — 2026-09-28

Digital and AI-supported work has changed how leaders communicate with employees, particularly in virtual, remote and hybrid settings. Although communication is widely discussed in digital leadership research, the literature uses different terms to describe what leaders need to communicate effectively. This scoping review maps leadership communication competencies and related communicative dimensions reported in digital and emerging AI-enabled workplace research. Guided by the Population-Concept-Context (PCC) framework, a Scopus search was conducted for journal articles published between 2020 and 2026 in Business, Management and Accounting. The search returned 71 records. Title and abstract screening resulted in 35 Include, 23 Uncertain and 13 Exclude records. Because the review was designed as abstract-level evidence mapping, the 23 Uncertain records were retained together with the 35 Include records, giving 58 records for analysis. Four recurring areas were identified: digital and media communication competence; relational and socio-emotional communication competence; adaptive communication competence; and communication for coordination and information exchange. The findings indicate that digital leadership communication involves more than using communication technologies. Leaders also need to make appropriate media choices, maintain relationships, adjust their communication to changing work conditions, and support information and feedback exchange. Evidence dealing specifically with AI-enabled workplaces remains limited. Emerging studies suggest that leaders may also need to interpret and explain AI-generated information, although it is too early to determine whether this represents a distinct communication competency. The review brings together a fragmented body of research and provides an organising basis for further work on leadership communication in digital and AI-enabled workplaces.

DIGITAL TRANSFORMATION IN HIGHER EDUCATION AND THE DEVELOPMENT OF STUDENT LEARNING ADAPTABILITY: A REVIEW OF CONTEMPORARY LITERATURE AND BIBLIOMETRIC TRENDS

Hui Zhao — 2026-09-07

Digital transformation has become a dominant agenda in higher education worldwide, fundamentally changing educational practices, institutional management, and student learning experiences. The integration of digital technologies has accelerated the adoption of online learning, blended learning, intelligent educational systems, and data-driven pedagogical approaches. Consequently, students are increasingly required to demonstrate learning adaptability in response to rapidly changing educational environments. This paper presents a bibliometric and thematic analysis of contemporary literature related to digital transformation, digital literacy, and learning adaptability in higher education. The study draws upon bibliometric data from Web of Science (WoS) and China National Knowledge Infrastructure (CNKI) to examine publication trends, emerging research themes, and intellectual structures within the field. The findings reveal substantial growth in scholarly attention toward digital transformation, digital literacy, and adaptive learning over the past decade, particularly following the COVID-19 pandemic. However, the analysis highlights a persistent fragmentation in existing literature, where digital literacy and learning adaptability are often examined as separate constructs rather than as interconnected dimensions within a digital learning ecosystem. In addition, the review identifies a significant research imbalance, with most studies focusing on macro-level institutional and technological developments, while micro-level student learning experiences remain underexplored, especially in the Chinese higher education context. This paper further proposes that learning adaptability should be understood as a key outcome influenced by digital literacy within digitally transformed learning environments. The study concludes by highlighting the need for more integrated theoretical frameworks that connect digital competence development with adaptive learning capabilities to support sustainable digital transformation in higher education.

TECHNOPHOBIA AND DIGITAL LITERACY IN DIGITAL ZAKAT WEBSITE DESIGN: A REVIEW OF BARRIERS, DESIGN STRATEGIES, AND RESEARCH GAPS

Jasmin Ilyani Ahmad — 2026-09-20

Limited digital literacy is an empirically confirmed barrier for adopting digital zakat, whereas technophobia constitutes a probable psychological barrier that has not been sufficiently investigated in relation to digital zakat. These factors are especially important for digital zakat websites since users need to combine their technological, financial, and religious skills. The aim of this narrative review is to provide synthesis of the literature on the adoption of digital zakat, digital literacy, technophobia, usability, accessibility, security, trust, website design, and institutional context. The literature review shows that there are existing connections between digital zakat adoption and digital literacy, facilitating conditions, trust, system quality, and information quality. There are also existing connections between technophobia and lower perceived ease of use and digital media literacy in other digital settings. As a result of the synthesis, the following potential barriers have been identified: navigation complexity, lack of guidance on how to perform procedures, problems with error recovery, security concerns, and mistrust toward institutions. The following design implications have been identified: simplified navigation, contextual guidance, design for accessibility, education of users, security information, and error recovery. However, the connection between the above-mentioned design interventions and website-level usability and technophobia has not been sufficiently researched empirically. Therefore, future research needs to experimentally validate interventions at the website level using diverse samples of users with limited digital literacy and non-users.

NAVIGATING CYBERSECURITY AND TRUST BARRIERS: A QUALITATIVE STUDY OF AI MANAGEMENT IN THE UAE SECURITY SECTOR

Khalfan Abdulla — 2026-09-28

This qualitative research paper explores the interaction between cybersecurity vulnerabilities and trust barriers influencing artificial intelligence (AI) management practice in the United Arab Emirates (UAE) security industry, addressing a gap left by quantitative acceptance studies that have treated these barriers as independent variables rather than as interacting factors. The main conclusion is that low trust and cybersecurity vulnerability are not independent hindrances but support each other. AAn interpretivist, exploratory design used a purposive sampling strategy and semi-structured interviews with 35 participants comprising security professionals, AI managers, cybersecurity experts, and governance staff, and data were analysed thematically. The results indicate that AI-related vulnerabilities, particularly adversarial manipulation and data-integrity breach create opaque, unexplainable AI behaviour, to which individuals adjust with a contingent, multidimensional type of doubt instead of a broad-based technological scepticism. In security, governance has not yet been formalised as fast as AI deployment in comparison to more mature governance in service delivery fields like healthcare and municipal services and the most viable management solutions participants identify are hardening security and accountability-making instead of two distinct initiatives. The study introduces a reconceptualisation of trust in high-stakes AI environments that is founded on multidimensional, offering technological, human, and organisational fields and recommends that governance formalisation should be seen as a step toward, rather than a follow-up to AI deployment by UAE security organisations and regulators.

DEVELOPING AN ENTITY–RELATIONSHIP DATA MODEL FOR GIS-BASED ANALYSIS OF RECREATIONAL PARK ACCESSIBILITY AND DISTANCE FROM RESIDENTIAL AREAS

Norsyazlin Mohd Rosli — 2026-09-10

Recreational parks play an important role in promoting physical activity, social interaction, environmental sustainability, and healthy urban environments. The assessment of recreational park accessibility requires the integration of spatial and non-spatial datasets representing parks, residential areas, transportation networks, access points, and accessibility indicators. However, existing GIS-based recreational park accessibility studies have predominantly focused on accessibility measures, spatial equity, network analysis, and accessibility indices, while comparatively less attention has been given to the conceptual database structures required to organise and integrate the datasets underpinning these analyses. This study therefore develops an Entity–Relationship Data Model (ERD) as a conceptual GIS database structure for assessing recreational park accessibility and spatial distance between recreational parks and residential areas in Seri Iskandar, Perak. The proposed ERD is specifically designed to represent the spatial and attribute relationships required for park accessibility and distance/proximity assessment rather than to conduct the accessibility analysis itself. The database development process comprises the identification of required spatial and non-spatial datasets, formulation of entities and attributes, and identification of relationships among entities using Chen’s ERD notation. Five (5) core entities are identified: Recreational Park, Residential Area, Road Network, Park Access Point, and Accessibility Assessment. The resulting model establishes primary and foreign key relationships and provides a structured foundation for storing park characteristics, residential information, transportation network data, access locations, and accessibility assessment attributes such as distance and travel time. The proposed ERD is designed to support subsequent GIS-based proximity and network accessibility analyses. The primary contribution of this study is therefore a conceptual GIS database model that improves the systematic organisation, consistency, and integrity of data required for recreational park accessibility assessment. The model can be further implemented and adapted to support recreational park planning and accessibility assessment in other study areas.

AI-DRIVEN PERSONALIZATION OF LIBRARY CONTENT ON SOCIAL MEDIA: A LITERATURE REVIEW OF USER ACCEPTANCE AND ETHICAL CONCERNS

Zuraidah Arif — 2026-09-28

Artificial intelligence (AI) offers libraries opportunities to personalize social media content and enhance information services, but its use raises concerns about user acceptance, privacy, bias, transparency, and accountability. This study reviews the literature on AI-driven personalized library content on social media to identify factors influencing user acceptance, examine ethical concerns, and develop recommendations for responsible implementation. A structured literature review was conducted using Scopus AI. The findings identify perceived usefulness, ease of use, trust, personalization quality, privacy, transparency, and AI literacy as key considerations in user acceptance. Major ethical concerns include privacy, algorithmic bias, and misinformation. The review suggests that responsible AI personalization requires transparent data practices, user consent, human oversight, bias monitoring, and clear institutional policies. The study consolidates current knowledge on user acceptance and ethical considerations and provides practical directions for responsible AI implementation in library social media.

RAINFALL- DRIVEN SATELLITE-BASED MOBILE EARLY WARNING SYSTEM FOR LANDSLIDE RISK ASSESSMENT IN ULU KLANG, MALAYSIA

Norsuzila Ya’acob — 2026-09-03

Malaysia's equatorial tropical climate is characterised by high rainfall throughout the year, making the country particularly susceptible to rainfall-induced landslides. Landslides can have serious environmental and socioeconomic impacts including loss of lives, damage to infrastructure, damage to properties, and long-term psychological effects on affected communities. Geological factors coupled with intense rainfall have been identified as key factors in slope failures in many high-risk zones . However, existing landslide early warning systems in Malaysia are often limited by limited accessibility, reliance on ground-based monitoring infrastructure, or the lack of user-friendly mobile platforms that can provide timely risk information to the general public. This study presents a mobile early warning system based on satellite rainfall observations by integrating Global Precipitation Measurement (GPM) rainfall information with a cross-platform mobile application for near real-time landslide risk assessment. The GPM rainfall estimates were pre-processed into JSON format and analyzed using cumulative rainfall thresholds over daily, 3-day and 30-day periods before being visualised through a React Native mobile application. The processed rainfall information was implemented as a cross-platform mobile application accessible on Android and iOS devices. Functional testing showed successful processing of GPM rainfall inputs, implementation of the validated risk assessment model, generation of corresponding landslide warning levels, and visualization of rainfall conditions in an interactive mobile interface. The results demonstrate the potential of combining satellite rainfall observations with mobile technology to promote community-based landslide preparedness and provide a scalable approach to disaster risk reduction in Malaysia.

BEYOND SCREEN TIME: DIGITAL DEVICE USE, ADDICTION AWARENESS, AND SELF-REGULATION AMONG MALAYSIAN YOUTH

Jenn Yuan Lee — 2026-09-17

This article examines digital device use, addiction awareness, and self-regulation among youth in Malaysia through a structured cross-sectional online survey of 528 respondents aged 16–30, recruited using non-probability convenience sampling. The study does not assume that long screen time, by itself, indicates digital addiction. Instead, screen exposure is read alongside purpose of use, perceived risk, behavioural control, and negative consequences. Some 88.07% of respondents reported five or more hours of daily screen use, with smartphones and laptops forming the core of their digital routines. Communication and information search were the leading purposes of use, indicating that much of this engagement was functional and embedded in everyday activities. More than 82% associated digital addiction with an inability to leave screens, while 82.01% understood healthy screen use as balancing digital engagement with other activities. Self-regulation was less consistent: respondents valued balance and prioritisation, yet delayed bedtime, frequent checking, and difficulty reducing screen time remained evident. These patterns do not establish whether respondents were addicted; rather, they show why high screen exposure needs to be interpreted together with behaviour, perceived control, purpose, and consequences. On this basis, the article proposes a conceptual distinction among digital necessity, functional dependency, and digital addiction.

SOURCE CREDIBILITY AND USER BEHAVIOR IN THE DIGITAL INFORMATION AGE: A PERFORMANCE ANALYSIS OF GLOBAL RESEARCH PRODUCTION

Zuraidah Arif — 2026-09-28

Source credibility has become increasingly important in digital information environments, where users encounter information through social media, online platforms, and other digitally mediated channels to fulfil their information needs. This study provides a bibliometric performance analysis of global research on source credibility and user behaviour. The analysis included 1,046 publications published between 2015 and 2025. The findings demonstrate substantial growth in research output, with 59.27% of publications appearing between 2023 and 2025. The corpus accumulated 36,895 citations, averaging 35.27 citations per publication, with an h-index of 89 and a g-index of 167, indicating strong scholarly visibility and citation concentration. The findings establish a performance-based baseline for understanding the growth, scholarly impact, publication structure, and multidisciplinary development of source credibility research in the digital information age.

GENERATIVE AI ADOPTION FOR ACADEMIC LEARNING AMONG FOUNDATION STUDENTS IN MALAYSIA: AN APPLICATION OF UTAUT2

Nur Hidayah Md Noh — 2026-09-10

Generative artificial intelligence (GenAI) is becoming more common in education, particularly as students use AI tools to support their learning and academic work. Despite this growing use, little research has focused on what influences GenAI use among foundation students in Malaysia. This study examines students’ intention to use GenAI and their actual use of it for academic learning based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). A quantitative approach was used, with data collected from Malaysian foundation students through a structured questionnaire. The data were analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The results showed that performance expectancy, social influence, habit, and behavioural intention had significant effects, whereas effort expectancy, facilitating conditions, hedonic motivation, and price value did not significantly affect behavioural intention. Facilitating conditions and habit also had significant effects on actual use behaviour. Overall, the results indicate that foundation students are more likely to use GenAI when they see clear academic benefits, are influenced by their surrounding environment, and have developed regular usage habits. The study adds to existing GenAI research by providing evidence from Malaysian foundation students and applying UTAUT2 within a pre-university setting.

DIGITAL TECHNOLOGIES IN ASTRONOMICAL HADITH STUDIES: TOWARD AN INTEGRATIVE FRAMEWORK

Mesbahul Hoque — 2026-09-20

Astronomical Hadith Studies is a sub-discipline of hadith studies that deals with the analysis of prophetic traditions pertaining to celestial matters such as the sighting of the moon, the timing of the five daily prayers, the direction of qiblah, the occurrence of solar and lunar eclipses, the movement of seasons and other celestial bodies mentioned in hadith texts. HistoricIbrahimally, the methods employed in Astronomical Hadith Studies have included classical hadith verification, juridical analysis, and astronomical observation. With the advancement of digital technologies, there are several ways in which Astronomical Hadith Studies could be improved and expanded for both educational purposes and practical applications. Although digital technologies have increasingly been applied to Islamic studies and astronomical computation, limited research has examined their systematic integration, particularly within the field of Astronomical Hadith Studies. Therefore, main objective of this paper is suggesting an integrative approach to studying astronomical hadith. Using a qualitative conceptual literature-review approach, the study examines scholarly literature on Hadith sciences, Islamic astronomy, digital Islamic scholarship, and emerging astronomical technologies. The paper concludes with the need to develop an integrative approach to maximise the potential of digital technologies while preserving the core principles of the study of hadith and Islamic astronomy.

REAL-TIME TEMPERATURE MONITORING AND CONTROL OF A POWER INVERTER IN A WIRELESS POWER TRANSFER SYSTEM

Muhammad Izzat Arif Sulaiman — 2026-09-03

This study presents a real-time temperature monitoring and control system for a Class E inverter in a low-power wireless power transfer prototype. The system was designed to monitor voltage, current, temperature and output power while supporting zero-voltage switching and protecting the inverter from overheating. MATLAB Simulink was used to model the transmitter and receiver stages, while Proteus supported PWM generation, control logic, and PCB design. The hardware prototype integrated a microcontroller, MOSFET driver, MOSFET, resonant coil network, rectifier, temperature sensor, LCD display, relay-controlled cooling fan and ESP32-based IoT monitoring. Simulation and hardware testing confirmed high-frequency power transfer, rectified DC output, and automatic fan activation at the 37 °C threshold. The findings show that active thermal control improves the safety, stability, and practicality of low-power wireless power transfer systems.

BEYOND DIGITAL ACCESS: THE ROLES OF DIGITAL LITERACY AND PARTICIPATION IN PERCEIVED DIGITAL INFRASTRUCTURE READINESS

Mutiiah Mohamad — 2026-09-17

Digital transformation has become an integral part of regional socio-economic development; however, mere physical presence of digital infrastructure does not necessarily guarantee any substantial engagement with digital technologies. Utilizing the Technology Readiness Index (TRI) framework as the theoretical approach, this study assesses the impact of Digital Literacy, Digital Access, and Digital Participation/Learnability on Perceived Digital Infrastructure Readiness in Langkawi, Malaysia – popular international tourist attraction and emerging digital destination. A quantitative cross-sectional survey design with a quota sample was used for data collection. The data was collected from 248 adults, out of which 238 completed responses were included in the analysis after the process of data screening. Descriptive statistics, correlation analysis, and multiple linear regression were used for data analysis. Results suggest that all the three predictors show positive and statistically significant relationship with Perceived Digital Infrastructure Readiness in bivariate correlations. However, the multiple linear regression shows that Digital Participation/Learnability is the most significant predictor ( β = 0.439, p< 0.001), followed by Digital Literacy ( β = 0.328, p<0.004), while Digital Access did not have any significant independent impact ( β = 0.205, p = 0.056). It means that the perceptions about infrastructure readiness do not only depend on whether there is connectivity or equipment but also on individual capabilities to make use of and interact with technology. The main contribution of this paper is the development of an approach to digital readiness which is focused on people rather than on infrastructure. The implication from the results of the research for practice is that the regional digital strategy in touristic destinations should take into account both hardware and digital literacy factors.

ASKME247: AN AI DRIVEN PEDAGOGICAL INNOVATION FOR HIGHER EDUCATION IN MALAYSIA

Anum Shafeera Amdan — 2026-09-28

The concept paper introduces the notion of using AskMe247, an artificial intelligence-powered tool created to help IMC413 students acquire mastery in information searching and storing and the important. AskMe247 is designed to be a versatile, around-the-clock learning partner that brings together independent learning and classroom teaching. It is an application that helps simplify technical topics through self-directed learning via providing personalized feedback, guidance and explanations. This paper highlights the use of AskMe247 as an AI-enabled innovation in Malaysian higher education based on literature from abroad, policy framework in the country, and pedagogical philosophy.

AI-SMART GLASSES FOR THE INTELLIGENT WASTE MANAGEMENT SYSTEMS

Marizuana Mat Daud — 2026-09-10

In this paper, we develop and pilot a Smart Bin Management System that combines smart glasses and QR code scanning technology to enhance the urban waste collection system. The current waste management method is not well-suited to the problem of monitoring and data accuracy and so the operations are very expensive. Utilizing the computer vision and display capabilities of smart glasses, it helps waste management personnel to scan QR codes on the phone without the need of tools and allows waste bins to be identified and reported. In collaboration with KDEB Waste Management Sdn Bhd (KDEBWM) our project was designed and tested to see if this wearable solution works. A total of 203 QR codes were successfully scanned and detected with a 68.97% success rate. A detailed analysis suggests that the delays of images to scan over more than one minute were mainly due to hardware difficulties and not the cloud database or QR architecture. In particular, the continuous capture and streaming of data over Bluetooth Low Energy (BLE) caused system problems and caused the device to shut down immediately and the data to not be readable. We believe that the current smart glass system will have to be reworked to overcome such deficiencies, and the proposed framework is well established for future wearable industrial applications in municipal waste management.

FACTORS INFLUENCING THE ACCEPTANCE OF (AI)-DRIVEN SERVICE IN MALAYSIAN ACADEMIC LIBRARIES: CONCEPTUAL FRAMEWORK

Atiqah Al -Insyirah Hamdan Yusi — 2026-09-20

This study aims to examine the factors influencing user acceptance of artificial intelligence (AI)-driven services in Malaysian academic libraries. As libraries increasingly adopt AI applications such as chatbots, recommendation systems, and automated cataloguing tools, understanding user perspectives becomes critical to ensuring successful implementation and sustained usage. Grounded in the Technology Acceptance Model (TAM), this study proposes a conceptual framework that extends TAM’s core constructs to incorporate accessibility and user satisfaction, in order to explain users’ behavioural intentions toward AI-driven services. A quantitative research design will be employed using an online questionnaire consisting of closed-ended items measured on a five-point Likert scale. Data will be collected from users at three Malaysian academic institutions, Universiti Teknologi MARA, Universiti Malaya, and Sunway University. The data will be analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS to assess both the measurement and structural models. This study is expected to identify the factors that influence the acceptance of AI-driven services among academic library users, with accessibility, perceived usefulness, and user satisfaction expected to play crucial roles in shaping this acceptance. By extending the Technology Acceptance Model within a developing country context, this study will contribute to the limited body of knowledge on AI adoption in Malaysian academic libraries. The findings are expected to provide practical insights for library administrators and policymakers to design user-centered AI strategies and enhance digital service delivery.

CONFIDENCE-WEIGHTED MID-LEVEL LIDAR–STEREO FUSION WITH HYBRID PCA-K-MEANS CLUSTERING FOR MARITIME 3D OBJECT DETECTION

Muhammad Aiman Norazaruddin — 2026-09-15

Autonomous Unmanned Surface Vessels (USVs) operating in nearshore environments require robust perception systems capable of handling challenging maritime conditions. However, LiDAR and stereo vision each suffer from complementary limitations: LiDAR produces sparse and reflection-sensitive measurements, while stereo vision provides dense depth estimates but performs poorly under occlusion and weak-texture conditions. While early- and late-fusion approaches have been widely explored, mid-level fusion strategies that preserve cross-modal feature interactions while adapting to sensor uncertainty remain underdeveloped for maritime perception. This paper introduces M-ACF Net (Maritime Adaptive Confidence Fusion Network), a confidence-adaptive mid-level fusion framework that dynamically integrates sparse LiDAR and dense stereo features based on pixel-level reliability. The fused representation is processed using PCA-K-Means clustering to generate orientation-invariant obstacle representations for Guidance, Navigation, and Control (GNC). The framework was implemented on an instrumented USV platform and evaluated on a multimodal dataset of 17,634 synchronised LiDAR–stereo–GNSS samples collected across three nearshore Malaysian sites under wave heights of 0.1–0.5 m. Across different wave conditions, M-ACF Net reduced depth-estimation RMSE by 44–60% compared with LiDAR-only measurements. The framework achieved 82.6% 3D Average Precision for ship detection under easy conditions and outperformed YOLOv8-Stereo, PointPillars, Pseudo-LiDAR, Frustum PointNet, and DSGN baselines, while matching DBSCAN's clustering quality at less than half its computation time and sustaining 18 frames per second on an embedded NVIDIA Jetson Orin NX. Field trials further validated real-time obstacle detection under operational conditions. These results demonstrate the effectiveness of confidence-adaptive mid-level fusion for real-time maritime obstacle perception.

FUZZY LOGIC FOR MANAGING COMPLEX UNCERTAINTY IN PREDICTIVE AND DECISION SUPPORT SYSTEMS

Norliana Mohd Najib — 2026-09-28

This paper addressed how fuzzy logic can represent and handle uncertainty across diverse prediction and decision-support applications. Six fuzzy logic systems were examined, covering case of diabetes risk prediction, personalized diet recommendation, rainfall prediction, supply-demand identification in online food delivery, educational decision support, and air quality assessment. For each case study, relevant characteristics were extracted, including uncertain input factors, membership function selection, fuzzy rule bases, inference process, and output interpretation. The analysis was conducted to identify recurring and specific patterns in the representation of uncertainty processing. The findings reveals that fuzzy systems across the six applications share a common reasoning structure that transforms imprecise input information into interpretable outputs through membership functions, rule-based reasoning, and fuzzy inference, while differing in the selection of uncertainty-related variables, membership function configurations, and rule structures according to case requirements. Based on the identified patterns, a generalized uncertainty-aware fuzzy inference framework is projected to illustrate the systematic progression of fuzzy reasoning to interpretable prediction, recommendation, assessment, or decision-support outputs. The findings also demonstrate the adaptability of fuzzy logic in representing gradual and imprecise information across diverse application domains. The proposed framework provides a conceptual foundation for the development of future fuzzy inference systems and offers practical guidance for researchers and practitioners developing for uncertainty-based applications in the future endeavours.