Journal of Information Systems and Digital Technologies

AI FROM AN ISLAMIC PERSPECTIVE

2025-09-13T14:59:03+08:00

This paper explores Artificial Intelligence (AI) from an Islamic ethical perspective by drawing upon the Qur’an, classical tafsir, and contemporary scholarship. Rather than treating AI solely as a technological or theological issue, the paper highlights how Islamic principles—justice, accountability, remembrance (dhikr), reflection (fikr), and gratitude (shukr)—can guide the ethical development and use of AI. Using a descriptive research design, the study synthesizes global concerns about AI, including bias, manipulation, and autonomy, with Islamic teachings on morality, responsibility, and societal well-being. The objective is to propose a framework that integrates AI ethics with Islamic epistemology, offering guidance for Muslims and contributing to broader discussions on responsible AI.

AN INTELLIGENT SYSTEM TO IDENTIFY FAKE VIDEOS ON ONLINE SOCIAL NETWORKS USING MACHINE LEARNING

2025-09-22T13:54:11+08:00

Advances in emerging technologies have led to the wide dissemination of fake videos on online social networks. This research employs the hybrid machine learning and deep learning algorithms to recognise video forgery on social media. This research presents a hybrid deep learning and machine learning approach for detecting manipulated videos. The proposed model employs the OpenCV deep neural network (DNN) face detector to locate facial regions in video frames, after which a pretrained ResNet50 convolutional neural network is applied to extract deep features, and a Support Vector Machine (SVM) is used to classify authentic and fake content in a binary fashion. The model was trained and evaluated on a dataset of publicly available 128 short-form videos gathered from TikTok and Facebook platforms. The five-fold stratified cross-validation results generated an average accuracy of 89.1%, precision of 87.6%, recall of 96.1%, F1-score of 91.5%, and an AUC of 0.95 for the SVM model. Furthermore, the comparative analyses showed that SVM outperformed Logistic Regression, Random Forest, Gradient Boosting, and K-Nearest Neighbour classifiers. The findings demonstrate that combining automated face detection with deep feature extraction and classical machine learning significantly improves fake-video detection and contributes to preserving authenticity in digital communication.

ADVANCING SUSTAINABLE WASTE MANAGEMENT ON CAMPUS THROUGH AN INTELLIGENT REVERSE VENDING MACHINE

2025-09-03T14:01:10+08:00

Global plastic pollution poses a critical environmental threat, impacting Sustainable Development Goals (SDGs) related to responsible consumption and climate action. Inconsistent recycling habits, particularly within high-consumption environments like university campuses, significantly contribute to this issue. Single-use plastic bottles are a major campus waste component, often ending up in landfills, exacerbating environmental degradation. This highlights an urgent need for innovative, engaging recycling solutions within educational settings and beyond. To address this, we developed an AI-driven Reverse Vending Machine (RVM) prototype and a cross-platform mobile application. The RVM utilizes a Raspberry Pi 4 as its central control unit, integrating capacitive proximity, photoelectric, ultrasonic, and infrared sensors for comprehensive bottle detection and monitoring. The system employs a YOLOv5 model for object detection, trained on a robust dataset of 2,000 labelled images, and a Flutter-based mobile application for user interaction and reward redemption. The development followed an Agile methodology, emphasizing iterative testing and refinement. A campus pilot study confirmed the system's efficacy. The YOLOv5 model achieved high accuracy (99.0% mAP@0.5, 98.4% precision, 96.8% recall). The system was highly responsive, with a detection-to-reward cycle under 1.2 seconds. User feedback was positive (SUS score: 81.3), and a student survey showed 76% willingness to use the RVM, with 48% motivated by vouchers, indicating strong acceptance and potential for behavioral change. This AI-driven RVM offers a technically feasible and highly accepted solution for sustainable waste management, providing an effective, user-centric approach to combat plastic pollution and offering a blueprint for broader global recycling efforts.

A CONCEPTUAL VIRTUHOME BUSINESS MODEL

2025-09-22T13:55:09+08:00

This paper introduces VirtuHome, a conceptual business model that leverages VR (Virtual Reality) and AR (Augmented Reality) technologies to transform the real estate experience and wellbeing. VirtuHome offers a digital platform and mobile application that allows customer segment (CS) like home buyers and renters, real estate developers, and property investors to explore properties virtually, enhanced branding through technology and foresee the real-time market insight. The platform addresses the key challenges faced by these CS by providing features like immersive virtual tours, interactive AR home staging, and remote live consultations. The methodology applied in this project is the Design Thinking (DT), which involves understanding the CS needs through literature review, benchmarking similar business like iProperty, Property Guru, and interviews. This is followed by ideation, prototyping, and validation using business modeling tools such as the Business Model Canvas (BMC) and Value Proposition Canvas (VPC), Business Environmental Map (EM), and Strategy Canvas (SC) to establish the validated business model of VirtuHome. Key findings reveal the significant potential of VirtuHome in enhancing CS’s experiences and wellbeing to improve convenience; optimise costs, time, and energy; and support smarter property decision-makings. Future work includes expanding the platform's features with AI and analytics, and developing a comprehensive business plan based on the validated VirtuHome business model.

UNIVERSITY-OF-TOMORROW BUSINESS MODEL

2025-10-03T09:26:38+08:00

This paper presents a conceptual University-of-Tomorrow (UoT) business model for the International Islamic University Malaysia (IIUM), focused on harnessing and integrating digital capabilities and ecosystems, platforms and applications to address key challenges, pains, gains, and job-to-do of current IIUM (Current Organization - CO). The model is designed to meet the evolving needs and expectations of various customer segments (CS) including students local and international, continuous and adult learners, underprivileged and war-torn students, communities global and local, government, and industries, while sustaining institutional relevance in a digital and post-pandemic era. Using the Design Thinking (DT) methodology, the study incorporates a literature review and stakeholder interviews/surveys to understand current challenges and issues. It then constructs the CO’s business model, followed by the development of an initial IIUM UoT business model, using the Business Model Canvas (BMC) and Value Proposition Canvas (VPC) framework, and supported with the Environmental Map (EM). After validating the initial UoT business model through further stakeholder interviews, the validated IIUM UoT business model is established. Universities need to transform and must adapt to drive skills-led economic and ethically led transformation as emphasized by global shifts in higher education and the evolving digital economy. The validated IIUM UoT business model is then compared to IIUM CO business model, and other global best universities benchmarked using the Strategy Canvas - to highlight the key differentiation and value propositions of IIUM UoT. Key findings contribute a practical, stakeholder-aligned UoT model with integrated digital solutions, offering strategic options for IIUM and other institutional decision-makers. Future work will involve designing a detailed Digital Implementation Strategy Plan (DISP) to drive the full transition to the UoT.

DEVELOPMENT OF E-COMMERCE PLATFORM FOR POSTNATAL CONFINEMENT SERVICES

2025-04-22T08:08:02+08:00

Accessing reliable postnatal confinement care remains a challenge for many expectant women due to the fragmented nature of available services. Currently, there is no centralized platform that allows expectant women to efficiently search for, compare, and evaluate service providers. Information about caregiver qualifications, experience, pricing, and service availability is scattered across multiple sources, making the process time-consuming and often frustrating. The lack of verified reviews and recommendations further contributes to concerns regarding safety and service quality. This paper introduces Pantang.com, a Business-to-Consumer (B2C) e-commerce platform developed to streamline access to postnatal confinement services. Employing the Agile development methodology, the platform was iteratively designed based on continuous user feedback to ensure responsiveness to user needs. Key components of the development process include user requirement gathering through surveys, intuitive interface design, and the implementation of features to enhance usability and trust. Pantang.com offers comprehensive caregiver profiles, user ratings, and verified reviews to promote transparency and informed decision-making. Filtering tools allow users to search by location, price, and service type, while integrated booking and secure payment functionalities improve convenience and transactional safety. To ensure platform effectiveness, ongoing testing and iterative updates are conducted based on user engagement and feedback. By addressing existing market inefficiencies and leveraging digital innovation, Pantang.com provides a centralized, user-centric solution for postnatal care. The platform aims to empower mothers with accessible, trustworthy, and efficient support during the critical postnatal period.

A CONCEPTUAL FRAMEWORK

2025-04-30T14:47:02+08:00

The current phenomenon of the interconnected digital world has heightened exposure to cyber risks, emphasising the critical need for robust cybersecurity risk management within organisations. Cybersecurity risk management encompasses identifying, assessing, and mitigating threats to protect individuals, organisations, and nations from cyber risks. Central to this process is the cybersecurity risk assessment, a fundamental exercise aimed at understanding and mitigating potential cyber threats. There are two primary risk assessment approaches: event-based and asset-based approaches. While current literatures are mostly focused on an asset-based approach, this study delves into the event-based approach by exploring potential cyber-attacks that could compromise the confidentiality, integrity, and availability of digital data, posing significant cybersecurity risks to organisations. Despite technological advancements and the increasing complexity of cyber threats, organisations’ predominant reliance on an asset-based approach to cybersecurity risk assessment may not adequately address the evolving nature of cyber risks. Furthermore, there is a lack of harmonisation between scholarly and established cybersecurity frameworks based on international standards, such as those by the National Institute of Standards and Technology (NIST) and the International Organisation for Standardization (ISO). This paper synthesises existing frameworks from ISO, NIST and academic research and proposes recommendations to guide organisations in implementing an event-based approach to cybersecurity risk assessment.

WOMAN HIJAB DETECTION USING TRANSFER LEARNING

2025-03-14T12:07:35+08:00

Person clothing is considered one of many important issues related to Islamic rulings (Sharia). One of these issues is the woman dress where an Islamic woman is required to keep consistent wearing of Hijab (veils) when she is outside. Based on Sharia and most of Islamic scholars, Hijab must cover woman’s hair, ears, and neck along with the top of chest. Classifying woman images into one who wearing Hijab or not can be significantly facilitated using the current approaches of deep learning. In this paper we proposed a structured method consisting of multiple steps for accurately classifying women’s images into Hijab and Non-Hijab by utilizing transfer learning approach of deep neural networks. We initially created a balanced and labeled dataset that includes 12,000 images from multiple sources, one half of the dataset for women wearing Hijab and the other for women not wearing Hijab. The dataset is then preprocessed for normalization techniques. After that we used three well-known pretrained models of transfer learning which are VGG16, Xception and MobileNetV2 to conduct our experiments. The feature extraction and fine-tuning strategies were used for examining the models. The selected models gave better performances when applying fine-tuning strategy where the accuracies values of 96.85%, 97.6% and 96.3% were achieved for VGG16, Xception and MobileNetV2 respectively. Our results proved the capability of transfer learning in detecting Hijab in women’s images in order to help individuals, institutions and others who are interested in Islamic dress.

ETHICS IN THE DIGITAL AGE

2025-02-04T14:42:47+08:00

This research paper delves into the ethical challenges arising from rapid technological advancements in the digital age, focusing on Islamic perspectives. It seeks to establish a comprehensive framework based on Islamic principles from the Qur'an, Hadith, and scholarly interpretations to guide human behaviour amidst these changes. While innovations like artificial intelligence, social media, and data analytics offer substantial benefits, they also present ethical dilemmas requiring careful consideration. The study examines challenges in areas such as privacy and surveillance, social media conduct, artificial intelligence, automation, and data security, exploring how Islamic ethics can guide individuals and communities in navigating these issues. Utilizing qualitative research methods, the study collects data from libraries, online sources, and researchers' experiences, which are then analysed to extract meaningful insights. By referencing relevant Qur'anic verses and authentic Hadiths, the study demonstrates the application of Islamic ethics to technological challenges. It explores various Islamic ethical frameworks, including maqasid al-shari’ah (objectives of Islamic law), fiqh al-mu'amalat (Islamic jurisprudence of transactions), and ijtihad (independent legal reasoning), to address these challenges. The paper recommends integrating Islamic ethical principles into educational curricula, professional codes of conduct, and technology-related policy frameworks. This integration is crucial for fostering ethical practices and decision-making, ensuring that technological advancements align with Islamic values and ethical standards. The study concludes that incorporating Islamic ethics into technology discussions enables individuals and societies to effectively navigate the digital age's challenges while upholding values that promote justice, truthfulness, and responsible conduct. It emphasizes the importance of understanding Islamic ethics in the context of the digital age to address contemporary ethical dilemmas and ensure that technological progress aligns with Islamic values.

SMECORP-OF-FUTURE

2025-09-19T05:22:28+08:00

This paper intends to present a business case for the strategic transformation SMECorp-of-Today (SMEoT) into SMECorp-of-Future (SMEoF). The business objectives of SMEoT are to meet the diverse needs and demands of various customer segments (CS) such as the Micro, Small and Medium Enterprise owners and entrepreneurs (MSMEs); Government; Company; and Zakat centres in seizing opportunities and to remain relevant in the digital economy. This paper adapts the Design Thinking (DT) methodology, encompassing conducting literature review (LR), benchmarking, and interviews to understand and define problems of these CS. For example, MSMEs extreme pain is having difficulty in getting loans or grants and the essential gain is to access to loans and grants according to their needs. Based on the literature review and benchmarking conducted, the initial business model prototype was developed using Business Model Canvas (BMC), Value Proposition Canvas (VPC), and Environmental Map (EM). Then the initial business model was validated with the customer segment and a Strategy Canvas (CS) was also developed to compare and validate SMEoF business model against the current model SMEoT. The key finding of this paper is the conceptual SMEoF business model, to facilitate digital transformation from SMEoT to SMEoF, financial inclusion, specific reskilling–upskilling programs, as well as access to global markets. The main contribution of this paper is to validated BM of SMEoF with current BM, inclusive and future-ready framework that places SME Corp Malaysia at the forefront of SME development. Future works include developing a Digital/IT Strategic Plan (DISP) to guide SMEoT holistic digital transformation by aligning strategies to the national policies like MyDigital, NEP 2030, National 4IR Policy and SME Corps Malaysia Business Strategic Plan 2022-2030 in the future work.