Journals of Universiti Tun Hussein Onn Malaysia (UTHM)
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Regulatory Framework of Fintech Ecosystem for Mobile Money Operator Performance in Nigeria
Full text linkThe mobile money operator\u27s explosive growth and evolution have had a big impact on how mobile money firms operate. It is still unclear, though, exactly how the fintech ecosystem and the organizational effectiveness of mobile money operators are related and how the adoption of Fintech solutions by mobile money operators will impact its growth. Hence, this study examines the impact of regulatory framework of fintech ecosystem on the performance of mobile money operators. Specific objectives are to; assess the impact of external guidelines, data privacy laws, and consumer protection measures on the growth of mobile money operators. A descriptive case study was used to assess 386 mobile money operators’ employees across 15 fintech mobile money firms which were selected through Multi stage sampling. PLS-SEM was used to analyze the data collected for the study. The findings of the study revealed that regulatory framework of fintech ecosystem dimensions; Data Privacy Laws (β=0.336, t=5.951, p<0.001), External Guidelines (β=0.292, t=5.292, p<0.001), and Consumer Protection Measures (β=0.256, t=4.814, p<0.001) all demonstrate positive significant influence on growth of mobile money operators. The study concluded that regulatory framework of fintech ecosystem has positive significant effect on mobile money operator performance. It therefore recommended among others that mobile money operators should implement comprehensive data privacy frameworks to enhance privacy-focused initiatives, including regular security audits, data protection training, and privacy-by-design implementations
The Effect of Techno-Stress on Labour Management Relations
Full text linkThe rapid infusion of technology into the workplace has created a paradox in human resource management practice. As a result, there is a growing need to explore how techno-stress influences these relationships. The objective of this study is to determine the effect of techno-stress on labor-management relations. The study used a cross-sectional survey design. The target population comprised 319 employees of the Kwara State Internal Revenue Service (KW-IRS). A sample size of 178 samples was determined via Krejcie and Morgan\u27s sample size formula while random sampling technique was used. The finding reveals that techno-stress significantly undermines labour–management relations, which positively influence organizational performance, while techno-stress shows no significant effect on employees’ work–life balance. The study concluded that techno-stress can lead to psychological and physical strain. It is then recommended that organizations should encourage a healthy work-life balance and introduce stress management programs and resources
Constructing an Islamic-Based Medical Worldview
Full text linkWhile many muslim majority countries have launched initiatives such as Islamic input in medical curriculum, Ibadah-Friendly Hospitals and Shariah-Compliant Hospitals to embed Islamic values in healthcare, modern medicine continues to be dominated by secular worldview. This paper argues that the integration of Islamic principles into medicine has largely been superficial because it is not founded upon an Islamic worldview (tasawwur). The result is worldview fragmentation, what may be called conceptual chaos between Islamic creeds and medical practice. This study constructs an Islamic-based medical worldview through qualitative research and document analysis. The framework reconstructs the foundations of medicine around seven key elements, that is Islamic creed (tauhidic), role (khilafah), knowledge, worship, ethics, God presence (Ihsan), and purpose. This study propose tasawwur as the foundation layer above existing hospital initiatives, forming a three-tier model that integrates worldview, regulation, and operation. This paper concludes that genuine Islamization of medicine must begin with worldview reconstruction rather than ethical or operational addition
Bridging the Gap: Aligning Vocational Graduates’ Competencies with Employer Expectations Using the KSAO Model
Full text linkIn response to growing concerns regarding vocational college students\u27 career issues, this study uses the KSAO model to investigate the competency gap between upper vocational accounting majors and employer expectations. This study identifies differences across important dimensions : knowledge (K), skills (S), ability (A), and other attributes (O) by using two set of instrument with four major indicators and 32 secondary indicators. The findings indicate that the satisfaction ratings of employers regarding students\u27 core competencies and the graduates\u27 self-assessments of their core competencies across all KSAO elements exhibit high mean scores. Findings show that the satisfaction rating of employers on the core competencies of students\u27 employment in descending order is other attributes > ability > knowledge > skills. On the other hand, graduates perceived themselves on the core competencies of students\u27 employment in descending order: knowledge > other attributes > skills > ability. There is a mismatch between employers’ perception and the graduated perception of the core competencies of students\u27 employment, and it is proven by the independent sample t-test. A strategy to enhance the core competencies of higher vocational accounting students through SWOT analysis was recommended as guidance for vocational institutions in strengthening talent development strategies and student core competencies, thereby contributing to bridging the gap between education and workforce needs
Root Cause Analysis Framework for Regulatory Compliance in Philippine Aviation Training
Full text linkApproved Training Organizations (ATOs) in the Philippines operate under the regulatory oversight of the Civil Aviation Authority of the Philippines (CAAP), which conducts annual audits to assess compliance with the Philippine Civil Aviation Regulations (PCAR) and ICAO Annex 1. Despite these inspections, recurring compliance gaps, particularly in documentation, instructional delivery, and internal quality assurance, suggest persistent systemic deficiencies. This study addresses these challenges by introducing a Root Cause Analysis (RCA)– based framework designed to strengthen regulatory compliance in aviation training institutions. Employing a qualitative case study design, the research analyzed CAAP audit reports, Corrective Action Requests (CARs), and internal quality documents from three ATOs. Methodological rigor was ensured through data triangulation, manual coding, and thematic analysis using NVivo software. RCA tools, including the 5 Whys and Fishbone Diagrams, were applied to trace visible deficiencies to underlying causes across organizational domains such as people, process, tools, and policy. The findings revealed institutional weaknesses in audit preparedness, instructional oversight, and quality monitoring that significantly contribute to compliance failures. The primary contribution is a systems-oriented RCA framework that embeds proactive compliance mechanisms within ATOs’ internal quality assurance functions, featuring a feedback loop linking RCA, CAPA escalation, targeted training, and internal audits. Policy recommendations are also proposed to enhance CAAP’s audit communication and CAP evaluation protocols, promoting a shift from reactive enforcement to developmental oversight. By positioning RCA as both an investigative and governance tool, this study offers a transferable model for enhancing regulatory resilience in aviation training systems across similarly regulated environments worldwide.
Human-Centered Design and Development of an Adjustable Crutch: Enhancing Usability and Functionality for Physical Disabilities
Full text linkCrutches are becoming more and more critical as the number of physically disabled individuals in a nation rises. The need for multidimensional and multivariate crutches to assist people with disabilities is more significant today. Before making a variant of the standard crutch, a proper study must be done to construct a stable crutch for high load-carrying capacity. Additionally, various crutch models are also available. A new challenge is the development of an entirely new crutch model. Numerous types of analysis were carried out in this research to create a reliable and effective product, including market analysis, quality function deployment, functional structure development, Kano model development, specification and design analysis, materials and manufacturing processes, and cost analysis. All facets of product development, such as consumer requirements, assembly schematics, and recycling practices, were explored in the study. The most intriguing additions were the product’s capacity to fold and the seating tool facility. A load analysis was conducted to meet this requirement, utilizing data from a survey of disabled persons employed in the business regarding the equipment required for people with physical challenges, especially when selecting materials. Another unique feature of our product is an adjustment system that helps the user to adjust its height. These features are new and thus make our product more memorable compared to existing products on the market. Ultimately, the product was developed and utilized successfully through the research
A Review of Machine Learning Used in the Diagnosis of Parkinson’s Disease
Full text linkParkinson’s Disease (PD) is projected to impact an increasing number of individuals due to the anticipated growth of the global elderly population. While there is currently no cure, early diagnosis remains crucial for extending the quality of life for individuals with PD. Machine Learning (ML) techniques have been found to be effective in facilitating remote monitoring and enabling early diagnosis of PD. ML algorithms have shown to be able to achieve higher accuracy diagnostics compared to experts, and there is still room for improvement. This paper aims to provide a comprehensive overview of recent developments in diagnosing PD using ML. The study investigates eight of the most widely used ML algorithms, namely Support Vector Machines (SVMs), Neural Networks (NNs), Ensemble Learning, K Nearest Neighbours, Logistic Regression, Decision Trees, Naive Bayes and Discriminant Analysis, to provide a thorough analysis of their applicability and effectiveness in PD diagnosis. This paper will focus on these algorithms as they are the basis of many other variants, and they are most popularly researched and used. The paper discusses the strengths and weaknesses of each algorithm, presents examples of their usage, and highlights their efficacy with different PD indicators. Moreover, this paper reviews some of the most influential works in recent years, identifying the most significant challenges in the field of PD diagnosis. It highlights how researchers have attempted to address them and outlines directions for future research. First, this paper reviews the ML techniques used in diagnosis of PD. Then, we discuss the ML models’ shortcomings and strength. Finally, we discuss the challenges and future directions in research of this field. Notably, the study shows that SVMs and NNs emerge as popular choices due to their efficacy with commonly used datasets in PD diagnosis
Experimental Investigation on Combustion, Performance, Emissions, and Vibrations in a Diesel-Hydrogen Dual-Fuel Engine with an On-Demand Hydrogen Generation System
Full text linkThe study addresses the challenge of onboard hydrogen storage in transportation by proposing an innovative solution involving an on-demand hydrogen generation system. This system operates via a chemical reaction between aluminum sulphate (Al₂(SO₄)₃) and sodium borohydride (NaBH₄), producing hydrogen gas in real-time. The research examines the performance of a Variable Compression Ratio (VCR) diesel engine running in a dual-fuel mode, where hydrogen is supplied from the reactor. Engine behaviour was systematically analyzed under varying operating conditions, including compression ratios of 16, 17, and 18, and engine loads ranging from no load up to 12 kg, increasing in 3 kg steps. Additionally, the hydrogen flow rate was adjusted between 0 and 15 liters per minute. The results indicate that the engine achieved its best performance, in terms of efficiency, combustion, emissions, and vibration characteristics, at a compression ratio of 18 and a hydrogen flow rate of 15 liters per minute. These findings offer valuable insights for the advancement of on-demand hydrogen reactors, highlighting their potential for integration with VCR diesel engines to promote cleaner and more sustainable transport solutions
Investigation on the Deposition of Conductive Ink on Multiple Substrates with Different Substrate Surface Energy and Ink Surface Tension Properties
Full text linkConductive ink is a transformative material that enables the printing of electronic circuits on a variety of substrates, revolutionizing the field of printed electronics. This study addresses the limitation of existing mathematical models for conductive ink deposition, which primarily assume ink deposition solely on generic substrates and printing on the fly, thus lacking adaptability for diverse applications. The objective is to integrate substrate surface energy and ink surface tension into mathematical model thus improve the precision of ink track width estimation. Employing a syringe deposition system, data analysis was conducted to develop an improved mathematical model that predicts ink deposition on various substrates while establishing optimal printing parameters. Experimental results indicated significant discrepancies in line widths, with initial measurements exceeding 2 mm and percentage errors surpassing 150%. By incorporating SSE, the improved model achieved line widths between 0.72 mm and 0.92 mm, significantly reducing the maximum error to 15.82%. The findings emphasize the crucial influence of substrate surface energy and ink surface tension on ink spreading and adhesion, particularly on substrates with varying porosity and absorbency.
Perceived Indoor Air Quality and Sick Building Syndrome among Work-From-Home Workers Using Geospatial Approach
Full text linkThis study aims to assess the associations between perceived indoor air quality (PIAQ) and several risk factors for sick building syndrome (SBS) among work-from-home (WFH) workers through appropriate statistical analyses. Using a geospatial approach, it also aims to identify the spatial correlation between PIAQ and SBS. The study was conducted among 131 WFH workers in Kuantan through a questionnaire survey. Multiple logistic regression was used to analyse the associations between the risk factors of PIAQ and SBS symptoms. The significant factors associated with the SBS symptoms were further analysed using a geospatial approach. The study found the prevalence of SBS by WFH workers in Kuantan was 75.6%. The most prevalent symptom reported was difficulty concentrating (42.7%), while nausea (9.2%) was the least prevalent symptom. There was no significant difference between gender and SBS symptoms. Findings showed associations between SBS symptoms and PIAQ climate factors such as draught 3.28 (1.01-10.59) and dust 2.82 (1.01-7.87). The geospatial approach of this study illustrates a visual mapping of the hotspot of SBS symptoms and the correlation between the risk factors and SBS. These findings underscore the importance of addressing IAQ issues among WFH workers to mitigate the occurrence of SBS symptoms.