Malaysian Journal of Science Health & Technology
Journal title Malaysian Journal of Science, Health & Technology Initials MJoSHT Abbreviation Malaysian J. of Sci. H. and Tech eISSN 2601-0003 (online) Frequency Two issues, approx. 22 articles per year (April and October) DOI Prefix 10.33102/mjosht - Crossref linked Editor-in-chief Professor Ts. Dr. Mohd Ikmar Nizam Mohamad Isa , Universiti Sains Islam Malaysia, Malaysia Managing Editor Dr. Azira Khalil , Universiti Sains Islam Malaysia, Malaysia Publisher USIM Press Citation Analysis Scopus | Google Scholar Peer Review Double Blind Review Sign up to our content alert emails to keep you updated on our latest articles. Sign Up
Penerbit Universiti Sains Islam Malaysia
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A Comparative Study of Principal Component Analysis with Ensemble Learning for Classification of Medical Data
Dimensionality reduction is a critical component in the analysis of medical data, specifically when addressing challenges like multicollinearity, noise, and high-dimensional feature spaces that can decrease classification performance. While principal component analysis (PCA) is a traditional choice, its utility in medical datasets is often hindered by outliers, corrupted observations, and low interpretability, as principal components are linear combinations of all original variables. This research compares PCA, robust PCA (RPCA), and sparse PCA (SPCA) integrated with random forest (RF) and extremely randomized trees (ERT). A simulation study revealed that while all PCA variants struggle with low class separation, RPCA and SPCA significantly outperform standard PCA in the presence of outliers. This study utilized a diabetes dataset that underwent thorough preprocessing, including median imputation, normalization, and the synthetic minority over-sampling technique (SMOTE) to address class imbalance. Model optimization involved cross-validation of the RPCA regularization parameter and the SPCA sparsity parameter based on the area under the receiver operating characteristic (ROC) curve (AUC). At the same time, RF and ERT hyperparameters were optimized using a two-stage random and grid search approach. Final empirical results demonstrate that the RPCA-ERT model is superior, achieving an accuracy of 0.8954 and a sensitivity of 0.9434, underscoring its effectiveness in managing contaminated medical data. VIDEO EXPLAINER AUDIO PODCAST
Mathematics, Statistics and Actuarial Science
Copyright (c) 2026 Siti Amirah Batrisya Mohd Rahaizi, Wendy Ling Shinyie, Soo-Fen Fam https://creativecommons.org/licenses/by/4.0
Halal Authentication of Gelatin: A Bibliometric Review of FTIR Spectroscopy and PCR Techniques
This research provides an overview of a bibliometric analysis of research on halal authentication of gelatin, with particular focus on the application of Fourier Transform Infrared (FTIR) spectroscopy as well as Polymerase Chain Reaction (PCR) techniques. The analysis was conducted using 71 journal articles retrieved from the Scopus database, covering the period from 2012 to 2025. VOSviewer software was used to analyse publication trends, citation patterns, keyword co-occurrence, and international collaboration among countries. The results indicate that research activity in this field has gradually increased over time, with a notable rise in publications in recent years, reflecting growing global interest in halal verification and food authenticity. Citation analysis shows that the most influential studies primarily focus on the development of FTIR and PCR-based analytical methods for detecting and identifying gelatin sources. Keyword co-occurrence analysis reveals two dominant research themes, namely spectroscopic analysis using FTIR and molecular detection using PCR techniques. In terms of geographical contribution, Indonesia and Malaysia emerged as the leading countries in publication output. At the same time, the co-authorship network demonstrates regional collaboration primarily among countries in Asia and the Middle East. Overall, the findings highlight the increasing importance of reliable analytical methods and international collaboration in strengthening halal authentication research and supporting the development of effective halal assurance systems.
Copyright (c) 2026 Norliyana Nordin, Shahrina Ismail, Norlelawati Arifin, Maryam Mohamed Rehan, Mohamad Azhan Yahya https://creativecommons.org/licenses/by/4.0
Simulation of a Photoacoustic-Based Gold Authentication System for Tungsten Inclusion Detection Using COMSOL Multiphysics
The increasing presence of counterfeit gold, especially with tungsten inclusions, poses a significant challenge to the authenticity of gold trading. This research presents a photoacoustic sensing (PAS) method for detecting tungsten inclusions in gold bars. Photoacoustic sensing leverages laser-induced acoustic waves to identify material discrepancies based on their thermal and optical characteristics. This approach enhances the detection capabilities by focusing on the photoacoustic response generated by the interaction of the gold and tungsten matrix with laser light, making it a more reliable and efficient non-destructive testing method. The proposed method is modelled and simulated using COMSOL Multiphysics, providing a simulation-based solution for gold verification. This research aims to contribute to the promotion of fair-trade practices by ensuring the authenticity of gold, aligning with the Sustainable Development Goals (SDGs), specifically SDG 8: Decent Work and Economic Growth, and SDG 12: Responsible Consumption and Production.
Copyright (c) 2026 Nur Izzatul Syahzanani Abd Ghani, Juliza Jamaludin, Marinah Othman, Irneza Ismail, Fatinah Rahalim, Mahfuzah Samirah Ideris, Firdaus Zaid https://creativecommons.org/licenses/by/4.0
Enhancing Cryptographic Resilience through Symmetric Encryption Algorithm Utilizing Variable Length Chromosomes Genetic Algorithm
Symmetric cryptography, particularly the Advanced Encryption Standard (AES), is widely used for secure data transmission due to its computational efficiency and strong encryption structure. However, limited internal randomness in AES makes it susceptible to advanced cryptanalytic attacks. To address this limitation, this research proposes an enhanced encryption approach that integrates Genetic Algorithm (GA) techniques into the AES framework to enhance randomness. The GA employs variable-length chromosomes and entropy-based fitness evaluation to evolve dynamic binary outputs through selection, crossover, and mutation operations. These evolved outputs are used to introduce controlled randomness into the encryption process, resulting in unpredictable and robust ciphertext. The expected outcome includes improved increased randomness, and stronger resistance to differential and linear attacks. In conclusion, the proposed GA-AES enhanced model offers a mechanism to strengthen symmetric encryption by introducing evolutionary randomness, making it more secure for modern data protection needs.
Copyright (c) 2025 Ahmed Jobaer, Nur Hafiza Zakaria, Farida Ridzuan, A H Azni https://creativecommons.org/licenses/by/4.0
Knowledge Integration Model of Blockchain Technology in Higher Learning Institutions: A Rasch Measurement Model Approach for Pilot Study
Blockchain technology has emerged as a transformative tool in higher education, offering secure, transparent, and tamper-proof systems for credential verification, academic record management, and institutional data governance. Despite its potential, adoption remains limited due to technical, financial, and organizational barriers, alongside a lack of validated measurement tools to assess readiness and integration. This pilot study aims to validate an instrument grounded in the Knowledge Integration Model of Blockchain Technology for Higher Learning Institutions using the Rasch Measurement Model. A 50 item survey was administered to 31 purposively sampled stakeholders, including academics, researchers, and postgraduate students with blockchain related experience. Data analysis using WINSTEPS 3.92.1 assessed reliability, item-person fit, unidimensionality, and targeting through Wright Map analysis. The results showed satisfactory reliability (person = 0.82; item = 0.77). Four items (B5, B6, D8, C7) exceeded the acceptable outfit MNSQ threshold (>1.5) and were revised to enhance instrument quality. However, several items showed misfit and require refinement, and the Wright Map indicated a need for more challenging items to better target high ability respondents. Unidimensionality testing revealed a dominant construct with minor secondary dimensions, suggesting further refinement for conceptual clarity. These findings provide preliminary evidence the instrument’s potential for large scale application, providing a foundation for assessing blockchain knowledge integration and guiding policy and strategic implementation in higher education.
Copyright (c) 2025 Nur Ilyana Ismarau Tajuddin, Nurafifah Mohd Nor, Nor Aziyatul Izni, Nur Idayu Ah Khaliludin, Aeshah Mohd Ali https://creativecommons.org/licenses/by/4.0
Used Palm Cooking Oil as Substrate for Optimization of Lipase Activity in Aeromonas caviae SS-2
Palm oil is widely used for culinary applications, industrial formulations, and oleochemical processing. The increasing demand for palm oil for household and industrial use indirectly contributes to environmental pollution, particularly through the unethical disposal of palm oil waste. In this study, a sustainable biotechnological approach is explored to utilize this waste by exploiting the catalytic potential of bacterial lipases. Lipase-producing bacteria have been isolated from used palm oil-contaminated environments in Nilai, Negeri Sembilan, using the stab agar screening method. Among 90 potential isolates, Aeromonas caviae SS-2 demonstrates the highest lipase specific activity at 9.189 µmol/mL/min within just 9 hours of incubation at 40℃. A. caviae SS-2 indicates an optimum lipase production when it is cultivated in Tryptone Azolectin Tween (TAT) broth supplemented with 1% (v/v) of Tween 40 and 2% (v/v) of used palm oil. This enzymatic biotransformation efficiently hydrolyzed long-chain triglycerides into shorter, value-added carbon chains, demonstrating its potential for lipid production and industrial bio-conversion.
Copyright (c) 2026 Azarul Afandi Suhaili, Siti Salhah Othman, Ismatul Nurul Asyikin Ismail, Aswath Rama Reddy https://creativecommons.org/licenses/by/4.0
Investigation of 0debug Stealer Using Assisted Static Analysis Method
This study investigates the capabilities of the identified 0debug Stealer malware through qualitative static analysis and reverse engineering. This study primarily employs non-executional static techniques, such as fingerprinting, decompiling, and string extraction, with a bit of dynamic analysis used primarily for deobfuscation. Analysis confirms that obfuscation hinders direct examination, yet reveals core functionalities of 1) anti-tampering, anti-VM, and anti-sniffer to evade detection 2) data theft targeting important victim information, and 3) Command and Control exfiltration. Findings demonstrate 0debug Stealer’s capabilities in bypassing traditional security measures, emphasising the critical role of static analysis in dissecting advanced threats. This paper contributes to the forensic analysis of emerging threats by providing a detailed examination of the 0debug Stealer's manner, revealing its evasion techniques and comprehensive data theft capabilities.
Copyright (c) 2025 Taqiyuddin Anas, Farida Ridzuan, Sakinah Ali Pitchay, Charles Lim https://creativecommons.org/licenses/by/4.0
Human Dimensions of Cybersecurity Operations: Survey Insights from SOC Professionals in Malaysia
Security Operations Centres (SOCs) form the operational core of cyber defence strategies across the world. They are tasked with ensuring continuous monitoring, triage, detection, and response to ever-evolving threats. However, conventional performance metrics used to evaluate SOC efficacy—such as Mean Time to Detect (MTTD), Mean Time to Respond (MTTR), and false positive rates—primarily assess system throughput while overlooking the psychosocial realities of the human analysts who underpin these metrics. This paper presents the findings of a quantitative workforce study conducted among 175 Malaysian SOC professionals across internal, hybrid, and managed security service provider (MSSP) environments. Using a Likert-based adaptation of the NIOSH Worker Well-Being Questionnaire (WellBQ), the study investigates stress, burnout, alert fatigue, task autonomy, psychological safety, tooling efficacy, and career development perceptions. Findings reveal that 73.1% of respondents experience emotional tiredness at least “Sometimes,” while 78.9% agree that more automation would improve their well-being. Notably, 68.0% reported having opportunities to grow and develop their careers within their SOC environments. These insights highlight the need for a paradigm shift in SOC performance measurement—one that integrates human-centric indicators alongside traditional technical KPIs. The paper concludes with empirically grounded recommendations for embedding well-being frameworks into operational security management to ensure sustainable, high-performing cybersecurity teams.
Security Operations Center (SOC); Human-Centric, Cybersecurity; Mean Time to Detect (MTTD); Mean Time to Respond (MTTR).
Copyright (c) 2025 Mohd Haffezal Md Yahaya, Najwa Hayaati Mohd Alwi https://creativecommons.org/licenses/by/4.0
Cancer Classification Challenges in High-Dimensional Microarray Data: An In-Depth Exploration of Machine Learning Models
Microarray gene expression profiling has transformed biomedical research by enabling large-scale, parallel analysis of thousands of genes. Despite its promise, cancer classification using Machine Learning (ML) on microarray data continues to face critical challenges, particularly due to high dimensionality, limited sample sizes, and severe class imbalance. These factors contribute to overfitting, poor generalization, and inflated performance metrics, hindering the clinical translation of models. This Structured Literature Review (SLR) examines ML-based cancer classification studies published between 2015 and 2025. This period was marked by the emergence of deep learning, synthetic data generation, and biologically informed modeling. Using a transparent selection protocol, we synthesize findings from over 20 peer-reviewed studies. The review focuses on three methodological pillars: biologically grounded feature selection, constrained data augmentation, and robust performance evaluation. We identify a growing trend toward hybrid feature selection methods that balance statistical relevance and biological interpretability. However, comparative benchmarking across datasets remains limited. Data augmentation techniques, such as Synthetic Minority Oversampling Technique (SMOTE) and Generative Adversarial Networks (GAN)s, are increasingly being adopted. However, they often lack biological validation. This raises concerns about the plausibility of synthetic gene profiles. To address this, we recommend integrating pathway-level constraints and gene ontology checks during the augmentation process. Furthermore, we observe that many studies disproportionately emphasize accuracy. This can misrepresent the model's efficacy in imbalanced settings. Metrics such as Matthews Correlation Coefficient (MCC), F1-score, and precision-recall curves offer more reliable insights. These metrics should be standardized across evaluations. External validation using independent datasets is also essential to assess generalizability. In addition, it helps mitigate dataset-specific bias. Based on the findings, we present a conceptual hybrid framework that integrates biologically informed feature selection, biologically constrained data augmentation, and balanced evaluation protocols. This framework is intended to enhance reproducibility, biological fidelity, and translational reliability in machine learning-based cancer diagnostics, thereby contributing to the advancement of precision oncology.
Copyright (c) 2025 Wafa' , Sakinah Ali Pitchay, Farida Ridzuan, Muhammad Harith Noor Azam https://creativecommons.org/licenses/by/4.0
An Improved Maturity Model for Electronic Court Case Management System from the Perspective of End Users in Malaysia
Many judicial systems are currently undergoing a significant digital transformation; however, there is no clear way to measure whether their Electronic Court Case Management Systems (ECCMS) are truly mature or not. In Malaysia, several nationwide court modernization programs have been underway. Since 2013, the end-user evaluation has remained somewhat fragmented. In this study, we propose an improved maturity model for an ECCMS and, after filtering out noisy and incomplete responses, test it on 300 active users from various Malaysian courts; 287 were used. The paradigm builds upon earlier e-government maturity models with four underlying constructs: second-order (1) human behaviour, (2) technological, (3) organisational factors, and (4) legal issues. Data were gathered using descriptive statistics, validity tests, and structural equation modelling (PLS-SEM), with a 5-point Likert scale. The structural model earned a Q²_predict value of 0.483 and an R² score of 0.8927, showing predictive power good but not perfect. Legal and regulatory aspects revealed, up to 0.713, the highest path coefficients, whereas technical and behavioural elements were marginally weaker. Although for further research there are still a few gaps, the accepted methodology provides a useful foundation for evaluating the development of e-justice. It can inform decisions about court digitalization, more data-driven.
Copyright (c) 2025 Adham M Alankar, Nurzi Juana Mohd Zaizi , Hanifah Abdul Hamid https://creativecommons.org/licenses/by/4.0
Bioactive Compounds of Salvadora persica (Miswak): Extraction, Characterization and Role in Tooth Decay Prevention
Miswak (Salvadora persica) has been widely recognized for its efficacy in promoting oral health and preventing dental issues. This study aimed to extract, characterize, and evaluate the active compounds in miswak using the maceration method. Chemical analysis reveals that miswak is rich in fluoride, silica, and benzyl isothiocyanate, which contribute to its antimicrobial, antiplaque, and anticariogenic properties. Methods were to extract and evaluate the active compound in miswak using Fourier Transform Infrared Spectroscopy (FTIR) and Ultraviolet-Visible (UV-Vis) Spectrophotometry and assessed its performance via eggshell test. FTIR analysis revealed the presence of phosphorus and calcium related compounds essential for dental health, such as calcium phosphate. Key functional groups, such as P-H at wavenumber 2323.50 cm⁻¹ and SI-O-C at wavenumber 1087.68 cm⁻¹ were identified in both powder and extract forms of miswak. Evaporation reduced the presence of phosphorus related compounds, potentially altering the chemical composition. UV-Vis analysis demonstrated higher absorbance values in original miswak at 25x and 75x dilutions compared to prepared miswak indicating a higher concentration of active substances. Electronic transitions in UV-vis indicated the presence of functional molecules vital for dental health. Performance tests using eggshells showed that miswak toothpaste protected against acidic environments (e.g., black coffee and carbonated drinks), reduced staining and emphasized its protective qualities due to fluoride miswak content. The findings also validated miswak as natural, cost-effective oral hygiene solution especially in resource limiting areas.
Copyright (c) 2026 Nur Fatihah Mohamad, Nusairah Ramli, Nurul Jannah Abd Rahman, Nadrahtul Huda Misral, Ummu-Hani Abas, Nor Haliza Mat Baharin, Juliana Jumal https://creativecommons.org/licenses/by/4.0
Identification of Key Parameters for Cover Audio Generation in Imperceptible Audio Steganography
The security of data during communication is an ever-growing challenge, as outdated algorithms face increasing vulnerability. Audio steganography offers a promising alternative by embedding data within audio signals in a manner that is imperceptible to human listeners. Recent advancements in cover selection as well as cover generation techniques have improved the quality and suitability of audio for embedding, yet the parameters influencing imperceptibility remain underexplored. This research aims to identify and evaluate key audio parameters which are energy, the total and value distribution of silent samples. These parameters can be assessed prior to the embedding process which offer a potential advantage over existing metrics, typically require post-embedding analysis to accurately assess imperceptibility. The methodology of this research consists of five main stages: parameter identification, dataset preparation, parameter extraction, embedding, and evaluation. Signal-to-Noise Ratio (SNR) was employed as the primary metric to assess perceptual transparency, with 20% data capacity embedded in each audio of total 220 audio. The first experiment revealed a positive correlation as high as r = 0.706 between energy and SNR, indicating that higher-energy audio benefit from auditory masking, resulting in improved imperceptibility. The second experiment showed a negative correlation, r = –0.787 between total silent sample and SNR, confirming that embedding in silent sample increases the risk of perceptible artifacts. Silent sample that has higher value exhibited superior SNR values compared to those with extremely lower value. These findings highlight the importance of pre-embedding analysis in identifying suitable samples for embedding. By identifying and evaluating these influential parameters, this research contributes to the development of intelligent cover generation strategies that enhance the transparency of audio steganography systems. The insights presented offer a foundation for future design, optimization, and real-world application of robust data-hiding techniques.
Copyright (c) 2025 Muhammad Harith Noor Azam, Farida Ridzuan, A H Azni, Sakinah Ali Pitchay, Nur Hafiza Zakaria https://creativecommons.org/licenses/by/4.0
Rapid Authentication of Pig Leather and Synthetic AlternRapid Authentication of Pig Leather and Synthetic Alternatives using NIR Spectroscopy and Chemometrics Approachatives using NIR Spectroscopy and Chemometrics Approach
This study investigates the discrimination between pig leather and Polyurethane (PU) leather using Near-Infrared (NIR) spectroscopy combined with chemometric techniques. Genuine leather derived from pig hides presents unique biochemical signatures linked to its collagen structure. In contrast, PU leather is a synthetic polymer engineered to replicate the visual and tactile properties of natural hides. Differentiating between these two materials is particularly crucial in industrial and cultural contexts, such as halal certification, where accurate authentication is crucial. Principal Component Analysis (PCA) was first employed as an unsupervised method to explore natural clustering. The PCA score plot revealed a clear separation between pig leather and PU leather, with the first principal component (PC-1) explaining 96% of the total variance, confirming that the dominant chemical features are sufficient for preliminary discrimination. For supervised classification, Partial Least Squares Discriminant Analysis (PLS-DA) revealed clear separation in the score plot. The model was supported by robust calibration and validation statistics, with high coefficients of determination (R² > 0.99) and low Root Mean Square Error (RMSE). Overall, these findings demonstrate that portable NIR spectroscopy, coupled with chemometrics, provides a rapid, non-destructive, and reliable authentication method with significant potential for industrial quality control, fraud prevention, and regulatory compliance.
Near-infrared spectroscopy; Chemometrics; Leather authentication, Halal authentication.
Copyright (c) 2025 Mohd Fared Abdul Khir, Ainil Hawa Mohamad Fauzi, Dzulfadli Rosli, Mohd Sukri Hassan, Norzaliman Mohd Zain https://creativecommons.org/licenses/by/4.0
Actuarial Reserve for Accumulated Leave Benefits (GCR) with Enhanced Mortality and Interest Rate Modeling
The 2023 Malaysian Budget increased the maximum compensable unused leave for public employees from 160 to 180 days, significantly raising future liabilities for public sector employers. Under the Malaysian Private Entities Reporting Standard (MPERS), universities must recognise these benefits, which are payable upon retirement or death, as actuarial liabilities. Existing tools, such as the Jabatan Perkhidmatan Awam (JPA) calculator, offer limited accuracy as they do not account for mortality risk or interest rate fluctuations. This study introduces an enhanced actuarial reserve model that incorporates both uncertainties. The model considers two payment casesw which are upon retirement and upon death, using survival probabilities, interest discounting, and assurance factors to determine the expected present value of future cash awards. To evaluate model performance, a simulation study using a non-parametric bootstrap is conducted on 5,000 simulated employee records. Bootstrap resampling is repeated at increasing levels to measure bias and consistency. Results show that both bias and variance decrease as bootstrap iterations increase, indicating model stability and accuracy. This improved model offers a more realistic and reliable method for estimating future cash awards, ensuring better financial planning, policy compliance, and reserve adequacy for higher education institutions.
Copyright (c) 2025 Nur Idayu Ah Khaliludin, Haslinawati Mohd Mustapha, Nur Ilyana Ismarau Tajuddin, Muhammad Nuruddin Sudin https://creativecommons.org/licenses/by/4.0
Toward Quantum-Resilient PKI: A Systematic Literature Review of Post-Quantum Certificates Model
The rise of quantum computing presents a critical threat to classical public-key cryptographic systems, necessitating a global shift toward post-quantum cryptography (PQC). While algorithmic standardisation has seen substantial progress since the National Institute of Standards and Technology (NIST) initiated its call for PQC proposals in 2017, the integration of these algorithms into certificate-based infrastructures remains fragmented and underexplored. This gap creates uncertainty for secure communication, particularly in transitioning legacy systems into quantum-resilient environments. This systematic literature review (SLR) focuses on PQC certificate architectures studied between 2017 and 2025, encompassing the evolution of the field since NIST's formal standardisation efforts began. The review employs the PRISMA 2020 methodology to identify and analyse six distinct post-quantum certificate models: Pure PQC, Hybrid, Composite, Chameleon, Parallel, and Wrapped. Each model is evaluated across several criteria, including structure, backwards compatibility, tooling support, standardisation status, and production readiness, drawing evidence from scholarly publications, draft standards, and open-source implementations. Findings highlight the Hybrid certificate as the most viable short-term solution due to its high interoperability and maturity in deployment. Composite and Parallel architectures offer enhanced security assurances that are suitable for critical infrastructure, although they come with increased implementation complexity. Pure PQC certificates, while future-proof, are still limited to constrained or greenfield environments. Chameleon and Wrapped models are identified as emerging alternatives for blockchain and legacy scenarios, respectively, with limited but growing support. This review enlightens the design and deployment of quantum-safe public key infrastructures by outlining the trade-offs and maturity levels of each architecture. It also emphasises the need for continued development in standardisation and toolchain support to facilitate scalable and secure PQC adoption.
Post-Quantum Cryptography (PQC), Public Key Infrastructure; X.509 Certificates; Certificate Verification; Hybrid Cryptographic Models
Copyright (c) 2025 Nor Azeala Mohd Yusof , A H Azni , Farida Ridzuan, Nur Hafiza Zakaria, Sakinah Ali Pitchay, Abdul Alif Zakaria, Tasnuva Ali https://creativecommons.org/licenses/by/4.0
Enhancing Audio Steganography Through CGAN-Generated Cover Audio and Adaptive LSB Embedding: A Hybrid Approach
Audio steganography hides secret messages inside audio files, enabling covert communication without drawing attention. Audio steganography methods aim to achieve high imperceptibility, robust performance, and high payload capacity. While traditional techniques like Least Significant Bit (LSB) coding offer good imperceptibility, they are highly vulnerable to statistical steganalysis and signal manipulation. Existing hybrid methods suffer from maintaining quality across diverse audio and inadequate robustness mechanisms, struggling to balance imperceptibility, payload capacity, and robustness. This paper proposes a novel hybrid approach that combines Conditional Generative Adversarial Networks (CGANs) with LSB coding to address these limitations. The CGAN is trained with the LibriSpeech dataset to generate audio patterns that simulate spontaneous speech for use as adaptive covers. The model was implemented using PyTorch, with performance evaluated based on Signal-to-Noise Ratio (SNR), Perceptual Evaluation of Speech Quality (PESQ), Bit Error Rate (BER), and robustness to audio transformations. Experimental results showed a PESQ value of 4.05 and a mean SNR of 33.1 dB, representing excellent audio quality given the substantial payload capacity of 1.27 kbps. The method achieved a BER value of 2.23% and 87% robustness to compression, filtering, and resampling operations. The effectiveness of the CGAN-LSB hybrid method for enhancing capacity, imperceptibility, and robustness is achieved through the CGAN's ability to generate statistically natural audio covers, while adaptive LSB integration preserves data integrity during signal processing operations, making it highly suitable for secure audio communication and audio watermarking applications. While the generated covers exhibit distributional properties similar to genuine audio, direct validation against specific steganalysis detectors remains an important direction for future empirical evaluation.
Copyright (c) 2025 Usman Ibrahim Musa, Farida Ridzuan, A H Azni, Nur Hafiza Zakaria, Ahmed A. AlSabhany https://creativecommons.org/licenses/by/4.0
Evaluation of User-Centred Design in the User Interface (UI) and User Experience (UX) of a Gamified Edutainment Application on Disaster Preparedness
Recent years have witnessed a rise in the frequency and intensity of natural disasters, disproportionately affecting vulnerable communities, as reported by the United Nations Office for Disaster Risk Reduction (UNDRR, 2022). Public preparedness, particularly among youth and rural populations, remains limited due to the absence of accessible and engaging educational tools. Conventional approaches often lack interactivity, reducing knowledge retention and behavioural change. To address these gaps, this study developed DisasterPrep, a user-centred mobile edutainment solution designed to enhance disaster awareness and preparedness. The research pursued three objectives: (i) to identify knowledge gaps among target users, (ii) to design a gamified mobile application tailored to their needs, and (iii) to evaluate its effectiveness in improving preparedness and resilience. A mixed-methods approach was adopted, including surveys, focus groups, and co-design workshops, followed by prototype testing with 30 participants in Malaysia. Quantitative data were collected through a structured survey measuring User Interface (UI) and User Experience (UX) using a 5-point Likert scale, with descriptive statistics computed for usability and engagement. Results revealed strong usability, with UI mean scores ranging from 4.04 to 4.60 and UX outcomes between 4.20 and 4.56. Tutorials, navigation flow, and progress tracking emerged as the most valued features, while simulation realism and quiz integration revealed more variable responses. Findings confirm alignment with Malaysia’s MySTIE strategic goals and contributions to SDG 3 (Good Health) and SDG 4 (Quality Education). This research demonstrates that gamified, user-centred mobile tools can significantly enhance disaster preparedness education, offering a scalable, inclusive model to strengthen community resilience. The novelty lies in integrating edutainment with structured evaluation, establishing a replicable framework for disaster education that bridges gaps in interactivity, engagement, and scalability.
Copyright (c) 2025 Sakinah Ali Pitchay, Farida Ridzuan , Najwa Hayaati Mohd Alwi, Azni A H https://creativecommons.org/licenses/by/4.0
A Pilot Feasibility Study of a Research Protocol Examining Predictors of Post-Traumatic Stress Symptoms among Malaysian Firefighters
Post-Traumatic Stress Symptoms (PTSS) among firefighters are an important concern, and identifying potential risk factors may assist organisations in better managing PTSS in this population. A larger study has been proposed to determine the prevalence and predictors of PTSS among Malaysian firefighters. This pilot feasibility study aimed to evaluate the newly designed research protocol, identify any issues pertaining to the questionnaires’ instructions and items, assess the data collection process, and determine the reliability of the instruments intended for the main study. This pilot study recruited firefighters from five fire and rescue stations in a state on the east coast of Peninsular Malaysia, using a cluster sampling approach. This cross-sectional study utilised both paper-based and online surveys to figure out the feasibility of subject recruitment, data collection methods, and data entry procedures. Measurement instruments were evaluated using Confirmatory Factor Analysis (CFA) and reliability analysis (internal consistency and two-week test-retest). Of the 108 respondents, 87% preferred the online questionnaire distribution method. Appropriate amendments to the research protocol, recruitment procedures, and data analysis plan were identified and deemed feasible for implementation in the main study. All instruments demonstrated acceptable values of Composite Reliability (CR), high internal consistency (Cronbach’s alpha values greater than 0.7), and moderate to excellent consistency of the Intraclass Correlation Coefficient (ICC) for test-retest reliability (ranging from 0.504 to 0.999). Overall, this pilot study supports the feasibility and reliability of the proposed research protocol for conducting the main study on PTSS among Malaysian firefighters.
Copyright (c) 2026 Huwaida Abdul Azis, Zairina A Rahman, Nizam Baharom, Mohd Radzniwan A. Rashid, Hamidin Awang, Nur Hafizah Mohammad Lukman https://creativecommons.org/licenses/by/4.0
Bioautography-Guided Thin Layer Chromatography and Fractionation of Garcinia mangostana Pericarp Extract for Antibacterial and Toxicity Evaluation
This study aims to explore the antibacterial activities of Garcinia mangostana pericarp (GMP) crude extract and partially purified extract. The antibacterial activity of both crude and partially purified extracts was assessed using Thin-Layer Chromatography (TLC) bioautography, Minimum Inhibitory Concentration (MIC), and toxicity assays. The GMP extract was separated via TLC using various eluents, including 5% ethyl acetate in petroleum ether, 1:3, 1:1, and 3:1 hexane:ethyl acetate, 1:1 hexane:diethyl ether, diethyl ether, 1:1 diethyl ether: methanol, Milli-Q water, and 0.1% formic acid in acetonitrile. A fractionation approach was used to evaluate the antibacterial activity of compounds present in the solvent fractions of the GMP extract. The antibacterial efficacy of the crude and partially purified GMP extracts was evaluated using MIC assays against B. cereus, C. perfringens, E. coli, L. monocytogenes, S. aureus, S. pneumoniae, and V. vulnificus. The GMP crude extract demonstrated the strongest antibacterial activity and the highest LC50 value (2.75 ± 0.15 mg/mL), indicating lower toxicity than partially purified GMP extracts. The L. monocytogenes was identified as the most susceptible microorganism to the GMP crude extract (MIC = 0.35 mg/mL), while B. cereus showed the least sensitivity (MIC = 11.25 mg/mL). These results support the potential use of GMP as a source of natural antibacterial agents, with possible applications in food preservation and safety. VIDEO EXPLAINER AUDIO PODCAST
Copyright (c) 2026 Zalikha Zamarudin, Muhamad Shirwan Abdullah Sani, Noor Faizul Hadry Nordin, Azura Amid, Amalia Mohd Hashim https://creativecommons.org/licenses/by/4.0
Advanced NLP Techniques for Generating Contextual and Grammatical Arabic Exam Questions
This paper outlines the development of an Arabic exam question generator that utilizes advanced Natural Language Processing (NLP) techniques and a comprehensive Arabic corpus. The primary aim is to aid educators in automating the process of crafting exam questions tailored specifically for A1-level Arabic learners. By harnessing the capabilities of NLP, the system integrates sequence-to-sequence (seq2seq) models and template-based methods to generate educationally appropriate questions. The seq2seq models are designed to predict the next word in a sequence, ensuring that the generated questions are natural and contextually fitting. This approach enables the system to produce logically coherent questions that align with the given context. Moreover, the template-based method guarantees grammatical accuracy, which is essential for educational purposes. The templates use as structured guidelines that steer the seq2seq models, ensuring that the questions adhere to proper grammatical rules and structures. A vital aspect of the system is the incorporation of the AraBERT pre-trained model. AraBERT, a transformer-based model customized for Arabic, undergoes fine-tuning with a specifically annotated dataset to adapt it to the task of generating questions from simple Arabic sentences, thereby enhancing its ability to handle the intricacies of the Arabic language. By combining seq2seq models for contextual relevance and template-based methods for grammatical precision, this dual approach effectively addresses the unique challenges associated with Arabic NLP. The richness of Arabic morphology and its syntactic complexity pose significant hurdles for NLP applications. Through the integration of these methodologies, the system ensures that the generated questions are not only contextually relevant but also grammatically correct, making it a valuable tool for educators. In conclusion, the paper discusses an innovative application of advanced NLP techniques and Arabic corpus utilization, providing a robust solution for automated Arabic exam question generation. This system holds significant potential for enhancing the efficiency and effectiveness of language instruction for Arabic learners.
Copyright (c) 2025 A H Azni, Farida Ridzuan, Najwa Hayaati Mohd Alwi , Sakinah Ali Pitchay, Zainur Rijal Abd Razak, Hanif Ridzwan Ahmad Rodzi, Ahmad A AlSabhany https://creativecommons.org/licenses/by/4.0
Impact of Long-Term Paddy Monoculture on Soil Microbial Diversity and Soil Macronutrients
This study investigated the long-term impacts of paddy monoculture on soil health in Tanjung Karang, Malaysia, through integrated physicochemical and metagenomic analyses, with comparisons to a pristine Raja Musa Forest Reserve (RMFR) reference site. Our findings demonstrate that prolonged monoculture significantly alters soil physicochemical properties of nitrogen, phosphorus, and potassium, thereby creating a distinct edaphic environment. Metagenomic analyses revealed a substantial increase in microbial diversity and richness in monocultured paddy soils compared to RMFR, with specific taxonomic groups becoming dominant. Crucially, functional annotation highlighted significant shifts in the abundance of genes associated with nitrogen, phosphorus, and potassium metabolism, underscoring the adaptive responses of the soil microbiome to continuous cultivation pressures and their influence on critical nutrient cycling processes.
Copyright (c) 2026 Muhammad Imran Jamaludin, Mohd Fadzli Ahmad, Hasdianty Abdullah, Tuan Badlishah Tuan Jusoh, Mohd Noor Mat Isa, Nor Suhaila Yaacob https://creativecommons.org/licenses/by/4.0
Speakable Me: The Development Of Speech Assistance Tools For Patients With Speech Disabilities
This project involves analyzing and designing a system that functions as an Augmentative and Alternative Communication (AAC) to help individuals with speech and language disorders (e.g., aphasia and dysarthria) who are unable to use verbal speech to communicate by producing sounds based on the words entered by users. The main objective of this project is to assist patients with various types and levels of speech disabilities in communicating their needs, achieving a higher rate of Words Per Minute (WPM) with minimal financial cost. This system is developed using React Native, Visual Studio Code, and Firebase. Speakable Me provides three categories of speech assistants. In particular, Category 1 allows patients to enter the words with full spellings, and the system produces sounds based on the words entered. Meanwhile, Category 2 uses Morse code, which is a combination of 1 and 0 that has been pre-determined and assigned to a word in the library. This category aims to help patients with limited movement since it only requires patients to use two fingers to press the keys. Following this, Category 3 is a category that uses pictograms and has limited keys. Each key represents basic sentences and words that patients usually use. Patients need to press one key, and the system will voice out the whole sentence. Speakable Me also provides a feature that allows patients or their caregivers to add their own words and pre-recorded voices to the library for Categories 1 and 2. While sentences and words for Category 3 can be replaced, they are limited to the ten keys of the numbered keyboard.
augmentative and alternative communication
Copyright (c) 2025 Noor Hayani Abd Rahim, Nadia Natasha Abd Aziz, Nur Izyan Rosli; Muhammad Hafizuddin Hamid https://creativecommons.org/licenses/by/4.0
The Role of Inflammatory Markers for Risk Stratification and Prognosis in Dialysis Patients: A Narrative Review
Chronic inflammation is a prevalent condition among dialysis patients and is associated with adverse health outcomes. This narrative review aims to provide a comprehensive analysis of the types and roles of inflammatory markers in risk assessment and their impact on the prognosis of dialysis patients. The associations between various inflammatory markers, including C-Reactive Protein (CRP), anti-inflammatory markers (IL-4, IL-10), and pro-inflammatory markers (TNF-α, IL-1, IL-6, IL-12), are evaluated in relation to their ability to predict mortality and cardiovascular complications in this population. Additionally, the potential of these markers for individualized risk stratification is discussed, aiding proper clinical decision-making and improving patient care. This review synthesizes current knowledge on inflammatory markers and their impact on the outcomes of dialysis patients, offering insights for improved prognostic assessment and therapeutic strategies.
Copyright (c) 2025 Siti Liyana Mohd Nor, Mohd Radzniwan A. Rashid, Faizul Helmi Addnan, Siva Gowri Pathmanathan, Nizam Baharom, Sharifah Najwa Syed Mohamad, Ruslinda Mustafar, Saharudin Ahmad, Arifa Mustika, Minidian Fasitasari, Lusito Lusito https://creativecommons.org/licenses/by/4.0
Microbial Diversity in Landfills through Metagenomics Profiling: A Review
Microbial communities are play a crucial role in the breakdown of organic waste, the production of biogas, and the reduction of environmental impact at landfills, which are complex ecosystems more than just places to dispose of waste. This study provides a comprehensive overview of the current knowledge of microbial diversity in landfills based on metagenomics studies. Metagenomics studies show that various microorganisms, including bacteria, archaea, and fungi, are found in landfills and interact to break down waste. Environmental factors such as pH, temperature, and waste composition impact these microbial communities. This review investigate how landfill age, waste composition, and operational methods impact microbial communities. Important microbial group functions in the waste breakdown, greenhouse gas emission, and soil leachate composition are also highlighted in this paper. The review examine how technologies, such as bioinformatics tools and high-throughput sequencing, enhance our knowledge of the landfill microbiome. Through metagenomics, researchers can identify the microbial genes responsible for important activities, including pollution bioremediation, production of methane, and organic matter breakdown. High-throughput sequencing methods such as 16S rRNA sequencing and shotgun metagenomics have improved the current understanding of landfill microbiomes by identifying new microbes with specialized metabolic roles. Identifying the plastic-degrading microbes and their enzymes is an emerging area of interest with potential for that may help develop biotechnological solutions to landfill plastic pollution. Metagenomics provides the opportunity to develop sustainable landfill management techniques and microbial-based waste treatment methods by identifying these microbial processes. This review emphasis the need of using the microbial processes for a better waste management and the significance of metagenomics in optimising landfill operations.
Copyright (c) 2025 Farah Aisha Mohd Haniff, Hasdianty Abdullah, Mohd Fadzli Ahmad, Maegala Nallapan Maniyam, Hazeeq Hazwan Azman, Nazahiyah Sulaiman, Nor Suhaila Yaacob https://creativecommons.org/licenses/by/4.0
Harnessing Green Nitrogen-Doped Zinc Oxide for Efficient Methylene Blue Dye Photocatalytic Degradation in Wastewater Treatment
Photocatalysis remains a promising solution for water treatment due to its efficiency, sustainability, and ability to degrade a wide range of contaminants. This study explores the green synthesis of zinc oxide (ZnO/GS) doped with varying weight percent of nitrogen (N) as a photocatalyst. ZnO/GS was synthesized via co-precipitation with zinc nitrate hexahydrate and papaya leaf extract in an aqueous solution, which will be further doped using urea as nitrogen doping. Characterization techniques, including FESEM, EDX, FTIR, and XRD, were employed to analyze the morphology, structural characteristics, surface, and pore volumes of nitrogen-doped green synthesized zinc oxide (N-ZnO/GS). The photocatalytic performance of these samples was evaluated through the photodegradation of methylene blue dye under visible light irradiation. The sample with 10wt%, which is 1 g of dopant, exhibited the optimal results, indicating a homogeneous surface and high crystallinity of N-ZnO/GS synthesized via co-precipitation, demonstrating the best photodegradation efficiency in the photocatalysis process. The findings suggest potential applications in environmental remediation through the degradation of organic pollutants, enhancing wastewater treatment efficacy.
Copyright (c) 2025 Ummu Humairah Hashim, Shahzulaikha Aiman Mohmed, Syahida Suhaimi, Maisurah Mukhtar, Nur Athirah Mohd Taib, Imam Tazi https://creativecommons.org/licenses/by/4.0
Application of Oven-Dried Durian Seed Powder and Freeze-Dried Durian Seed Powder on Extending Probiotics Longevity
Durian seed is often wasted but it can be utilized as a biopolymer and encapsulating agent for probiotics. This is good since it is a natural and sustainable biopolymer source. However, durian seed contains a lot of impurities that may hinder the biopolymer’s functional properties. This study aims to extract gum from durian seeds, subject them to oven-drying and freeze drying to obtain durian seed powder, study both oven-dried and freeze-dried durian seed’s characteristics and the potential to use them to enhance the growth of probiotics. Freeze-dried durian seed powder has higher yield percentage, higher water holding capacity, and higher oil holding capacity than oven-dried durian seed powder. Freeze-dried durian seed powder also has more pores and more uniform structure compared to oven-dried durian seed powder, which can be seen through scanning electron microscope. Both oven-dried durian seed powder and freeze-dried durian seed powder manage to support probiotics’ growth. The probiotics’ concentration can be seen to increase after 3 days of incubation upon encapsulation via dried durian seed flour for both encapsulated probiotics with oven-dried durian seed powder and encapsulated probiotics with freeze-dried durian seed powder. Freeze-dried durian seed powder support probiotics’ growth better than oven-dried durian seed powder since the concentration of probiotics after being encapsulated with freeze-dried durian seed powder is higher than the concentration of probiotics after being encapsulated with oven-dried durian seed powder. Based on observation via scanning electron microscope, encapsulated probiotics with freeze-dried durian seed powder also has better appearance, less wrinkles and less dents compared to encapsulated probiotics with oven-dried durian seed powder.
Copyright (c) 2025 Ahmad Naim Rohaizan, Latiffah Karim, Siti Radhiah Omar, Syamila Mansor, Nur Huda Faujan, Jeehan Nusair https://creativecommons.org/licenses/by/4.0
Sleep Duration and BMI: A Study Among First-Year Students of a Malaysian Muslim Gifted and Talented Institution
Sleep is widely recognized as a public health concern due to its impact on societal well-being and healthcare expenses. Emerging evidence suggests that insufficient sleep may significantly increase the risk of obesity and cardiovascular event. To date few studies have examined sleep duration and patterns within Malaysian boarding school particularly in Muslim Gifted and Talented institution. This study aims to identify sleep duration and investigate its relationship with body mass index (BMI) among first-year students of Kolej PERMATA Insan. Demographic data including gender, height, and weight were analysed using descriptive analysis. A linear regression test was applied to explore the relationship between BMI and sleep duration. Result indicated that male students slept significantly longer compared to female students. However, no association was found between sleep duration and BMI. This postulates that the structured environment and healthy lifestyle prepared by the Muslim Gifted and Talented Institution may mitigate potential negative impacts of insufficient sleep on BMI.
Copyright (c) 2025 Nur Fazidah Asmuje, Muhammad Nashwan Mohd Nasarudin, Abdul Razzak Khan Rustum Ali Khan, Rahayu Ahmad https://creativecommons.org/licenses/by/4.0
The Relationship Between Brain Wave Power Value Of Pain Perception And Empathy Using The Electroencephalogram (EEG)
Pain is said to be influenced by many psychological factors such as emotional state that manipulated the level of empathy. However, there are limited studies exploring the neuro-correlation connecting all these aspects. The current study aims to assess the dominant brain wave power value of pain perception and empathy by determining the area activated associated with the imaginary pain under three different categories which are stranger, one-self and loved-one. The study utilized a tool of brain signal detector (electroencephalography (EEG) device) which is Emotiv Insight focusing the relevant area of the brain (AF3, AF4, T7, T8 and Pz) to record the electrical signal of healthy subjects during the pain-visual-stimuli presentations. Images showing the pain condition were used as stimulus material during the EEG brain scanning session. The analysis was performed using Emotive Launcher and Brain Vision Analyzer version 2.2. Findings indicates the imaginary pain has activated the prefrontal area of the brain, specifically the medial frontal gyrus (MFG), superior frontal gyrus (SFG), orbital gyrus, subcallosal gyrus, and rectal gyrus; and revealing theta power band as the most dominant brain wave in this research. These power values also relate with the pain perception that influenced by the empathy level of individuals as observed, individual with high empathy do feel more pain for others. This outcome will help in understanding the mechanism of empathy and pain perception especially when imagining their loved one in pain that could enhance the research development in examining psychological processes.
EEG; Imaginary Pain; Empathy; Brain Wave; Power Value
Copyright (c) 2025 Siti Nur Aisyah Sazali, Muhammad Zaim Kashfi Zaman, Sofina Tamam, Eizan Azira Mat Sharif, Muhammad Ali Mustofa Kamal https://creativecommons.org/licenses/by/4.0
Analysis of Trust Models in Public Key Infrastructure: A Systematic Literature Review of Interoperability Challenges
Public Key Infrastructure (PKI) guarantees secure communication and authentication in digital contexts. With the expansion of digital ecosystems, the ability of PKI systems to work together smoothly becomes increasingly important, allowing multiple trust models to be compatible. Nevertheless, several significant challenges must be overcome when merging different trust models. The current body of research does not thoroughly examine these difficulties in various PKI trust models. This study aims to conduct a comprehensive assessment and analysis of the difficulties related to PKI interoperability. The focus will be on trust models such as Cross Certification, Bridge CA, Hierarchical, Hybrid, Cross Recognition, and Certificate Trust Lists. This systematic literature review (SLR) uses the PRISMA technique to analyse trust models in PKI interoperability. The review focuses on peer-reviewed studies published between 2000 and 2024, ensuring transparency and rigor. Eligibility criteria included studies using quantitative methodologies and sourced from major academic databases. This systematic review identified critical challenges in the interoperability of PKI trust models, particularly in operational complexity, security, liability, and scalability. Trust models like Cross Certification, Bridge CA, and Hierarchical systems each present unique challenges when integrated into diverse digital ecosystems. Moreover, gaps in the current research suggest the need for more standardised, scalable solutions that can accommodate the growing complexity of digital infrastructures. Future research should focus on developing a universal model for PKI interoperability, with a particular emphasis on large-scale environments such as E-commerce and E-government systems.
Key management System (KMS), Interoperability, Public Key Infrastructure (PKI), Comparative analysis
Copyright (c) 2025 Rozlinda Radzali, A.H. Azni, Farida Ridzuan, Nur Hafiza Zakaria, Tasnuva Ali https://creativecommons.org/licenses/by/4.0
A Maturity Model for the Accredited Food Laboratory in Malaysia: A Case Study
A Maturity Model (MM) is essential for laboratories aiming to improve and compete globally. Despite being accredited for over 20 years, some laboratories lack evidence of system maturity necessary for international competitiveness. A higher maturity level indicates a robust quality management system, leading to improved efficiency, accuracy, and customer satisfaction, while also assuring stakeholders, such as customers and regulatory bodies, of the laboratory's commitment to continuous improvement. The MM is designed to assess the success of laboratory processes, management styles, and the development of quality management practices, based on the 4M model (Manpower, Method, Machine, Material). The MM was developed using Analytes Accurate Certain Score (AACS) for the ten most common tests and System Maturity Scores (SMS), which incorporate proficiency testing and audit scores over two accreditation cycles (six years). While the model identifies inefficiencies, it helps organizations pinpoint areas of improvement and devise strategies to enhance their operations. This study applied the MM to a commercial laboratory, ABC (anonymized), accredited since the early 1990s and having undergone eight assessment cycles. The laboratory was found to be at a “leading” maturity level with a score above 80%, although improvements are still needed. Key areas for improvement include: 1) **Manpower**: maintaining competent staff by adjusting management strategies, 2) **Method**: validating all in-house methods according to Analytical Laboratory Accreditation Criteria Committee (ALACC) guidelines, 3) **Machine**: applying good laboratory practices (GLP) for equipment sharing, especially for specific analytes, and 4) **Material**: ensuring metrologically traceable reference materials and proficiency testing for all analytes. These improvements will help the laboratory further enhance its global competitiveness.
Computational Modeling & System Development
maturity model, analytes accurate certain scores, proficiency testing, audit/assessment scores
Copyright (c) 2025 Li Hui Ling, Mohd Sukri Hassan, Che Wan Zanariah Che Wan Ngah, Mehmet Ozturk https://creativecommons.org/licenses/by/4.0