Determinants of non-performing financing in local and foreign islamic banks in Malaysia: the moderating role of staff efficiency

Non-Performing Financing (NPF) levels recorded by 11 local and 5 foreign Islamic banks in Malaysia from 2017 to 2023 indicate fluctuations throughout that timeframe. High NPF may impact the financial performance of Islamic banks in Malaysia and effect the general financial stability of the country. This study examines the determinants that may influence the NPF levels of both local and foreign Islamic banks in Malaysia. It includes internal factors such as Return on Assets (ROA), Financing to Deposit Ratio (FDR), Bank Size, and Financing Loss Provision (FLP), and external elements like Gross Domestic Product (GDP), Unemployment Rate (UR), Inflation Rate (IR), and Control of Corruption (COC). This research also includes Staff Efficiency (STAFFX) as a moderating factor that affects the link between the independent and dependent variables. Staff Efficiency is important because if personnel do not work effectively (due to insufficient expertise), the performance of the bank is likely to be significantly impacted. The data for this study were sourced from the Fitch Connect Database, the Department of Statistics Malaysia, and the Worldwide Governance Indicator. This research employs Panel Data Regression Analysis with the Generalized Least Squares Method and a hierarchical regression model. The findings indicate that ROA, FDR, Bank Size, FLP, and UR significantly influence the NPF levels of local and foreign Islamic banks in Malaysia. Other predictors, namely GDP, IR, and COC have insignificant impact on NPF. This research also shows that Staff Efficiency can moderate and enhance the correlation between FDR and NPF in local Islamic banks, along with the links between Inflation Rate and NPF as well as COC and NPF in foreign Islamic banks. This study provides new interesting findings regarding the beneficial effect of Staff Efficiency in minimizing NPF during the unstable economic conditions

The optimization of ruminant feed with local ingredients using linear programming

The high cost of feed is a major factor that reduces profit margins in ruminant farming, primarily due to the reliance on imported feed pellets. However, various locally available ingredients present cost–effective alternatives that can still meet the nutritional requirements of ruminants. This study aims to create a cost–effective goat feed using local ingredients through Linear Programming (LP). The objective is to find the cheapest feed mix that still meets all the nutritional requirements. Eleven local ingredients from Kedah and Perlis were chosen for their availability, cost–effective, and nutritional value. Using Excel Solver, a LP model was formulated and solved to meet key nutrient needs for ruminants, specifically dry matter, crude protein, calcium, and phosphorus. Nutrient composition data for each ingredient were collected from The Malaysian Agricultural Research and Development Institute (MARDI). The results show that a balanced feed can be formulated using local ingredients, reducing reliance on imported feed and supporting sustainable farming in Kedah and Perlis. The LP model found an optimal solution using just two local ingredients, petai belalang and napier grass, that fully meet all nutritional needs. This approach resulted in a 72% reduction in feed costs compared to current commercial options. This research offers a practical solution for local farmers, enabling the production of ruminant feed at a lower cost and thereby enhancing profit margins. As a result, this contributes to improved food security, economic resilience in rural communities, and a more sustainable livestock industry

i-Synergy: An integrated predictive model of time pressure, personality types, gender, knowledge and task complexity to determine software developer’s performance

Human factors play a crucial role in software engineering (SE) as software is developed and utilized by people. One of the key reasons for software project failure is not assigning the right people to the right tasks during project planning. This issue becomes critical when developers work under time pressure (TP), often resulting in poor performance and delays. Each personality type approaches TP differently, and gender-based personality differences may further influence how developers handle TP, leading to varied outcomes. In addition, task complexity and developers’ knowledge interrelate with personality types and gender, potentially affecting project performance under TP. The main aim of this study is to propose the i-SYNERGY model by investigating the relationship between TP, personality types, gender, knowledge, and task complexity. To develop this model, empirical evidence was gathered from controlled experiments conducted with SE students, and generalised from industrial data through two case studies. The Myers-Briggs Type Indicator (MBTI) and NASA task load index (TLX) were used to measure personality types and TP, respectively. The data analysis was divided into two stages. The first stage involved examining factual figures of data to develop the model, while the second stage involved predictive experiments for developing the model under the knowledge discovery in databases (KDD) process. Five data mining techniques—artificial neural network (ANN), support vector machine (SVM), decision tree, K-nearest neighbor (KNN) and logistic regression were employed to identify the most suitable technique for model development. Logistic regression yielded the most significant results for developing the study model, confirming that personality types and gender differences influence software developers' ability to handle TP. This study offers empirical evidence regarding the impact of TP on humanistic aspects. Furthermore, the model developed can be leveraged to enhance the success rate of software projects in the field of SE

Work safety scale influcing safety behaviour in signaller army

This study investigates the factors influencing safety behaviour in the Signaller Army, focusing on Work Safety Scale (WSS) factors, including co-worker safety, supervisor safety, management safety practices, and satisfaction of safety programs. The primary objectives were to assess the level of safety behaviour, analyse how WSS factors influence safety behaviour, and identify which WSS factors has the strongest impact on safety behaviour. A quantitative survey was conducted, collecting data from 295 military personnel, including Officers and Other Ranks. The data was analyzed using SPSS version 28.0, employing descriptive statistics, Pearson product-moment correlation coefficient analysis, and multiple regression analysis. The results revealed that Signaller Army personnel exhibited a high level of safety behaviour, with a mean score of 3.893. All WSS factors showed a significant positive relationship with safety behaviour. Specifically, co-worker safety (r = 0.552, p-value < 0.001), supervisor safety (r = 0.931, p-value < 0.001), management safety practice (r = 0.923, p-value < 0.001), and satisfaction of safety programs (r = 0.779, p-value < 0.001) were positively correlated with safety behaviour. Multiple regression analysis revealed that supervisor safety (b = 0.456) was the most influential factor, followed by management safety practices (b = 0.410), co-worker safety (b = 0.118), and satisfaction of safety programs (b = 0.091). These findings emphasize the importance of leadership, effective organizational practices, and strong teamwork in promoting safety behaviour within the military. The study offers valuable insights into improving safety culture and behaviour in military contexts, highlighting the need for targeted strategies to enhance safety culture and reduce operational risk

Instructional design model of mobile augmented reality for enhancing comprehension, learning engagement and perceived motivation in students with diverse spatial visualization abilities

Despite various design models that have been proposed and adapted for mobile augmented reality (MAR) applications development, none has addressed the integration of comprehension, learning engagement, and perceived motivation elements in learning Computer System Organization (CSO) among polytechnic students’ students with diverse Spatial Visualization Abilities (SVA). This leaves a critical gap in the development of design models in educational technology for MARbased learning environments. This study aimed to develop and evaluate the Mobile Augmented Reality Instructional Design Model (MARID) for polytechnic students with diverse SVA. Based on the MARID model, two MAR applications were designed and developed; Mobile Augmented Reality Functional Realism (MARCO-FR) and Mobile Augmented Reality Physical Realism (MARCO-PR). Both were designed for the CSO course. A quasi-experimental factorial design was used to examine the effects of the independent variables of MARCO modes, which were the MARCO-FR and MARCO-PR on the dependent variables: comprehension, learning engagement, and perceived motivation, moderated by the students’ SVA. This study involved 200 polytechnic students who were assigned to use one of the MARCO modes. Research procedures included pre-tests, post-tests, expert validation, and alpha-beta testing. The data was analysed using descriptive and inferential statistics which is ANOVA. Findings revealed that students using MARCO-FR demonstrated significantly higher performance in comprehension, learning engagement, and perceived motivation compared to those using MARCO-PR, across both high and low SVA levels. High SVA students showed exceptional improvements in comprehension and learning engagement with MARCO-FR, attributed to its visual realism and emphasis on spatial procedural knowledge. Low SVA students also benefited from both MARCO modes, although their performance gains were more pronounced with MARCO-FR. This study highlights MARID as an effective instructional design model for MAR to address diverse learning needs. MARCO-FR is recommended for students across SVA levels, while MARCO-PR offers potential for broader applications. This research contributes to integrating MAR into instructional design for technical education and advancing educational technolog

The impact of computerized information systems on crisis management in UAE immigration services

The main objective of this study is to investigate the impact of computerized management information systems and their relationship to crisis management in the Passports and Immigration Department of the United Arab Emirates. The problem of the study focused on the challenges encountered in implementing computerized management information systems, specifically in the dimensions of System Quality (SYQ), Service Quality (SEQ), Information System Quality (ISQ), and Decision Making Speed (DMS). The study adopted quantitative approach and benefited from statistical evaluation based on detailed solutions and techniques of variance and covariance, correlation and regression. A questionnaire set was created from previous literary works and modified to match the study conditions. The study population were all employees who are working in the Department of Passports and Immigration of the United Arab Emirates. It was formed according to the Federal Center for Competitiveness and Statistics (9800) employees. The target sample size is 370, but the valid data set for analysis was 330 questionnaires. The results of the main dependent variable Crisis Management (CM) showed significant predictive power. This explained that the independent variables (system quality, system quality services, quality of information, speed of decision-making) in the proposed model accounted for 88% of the changes in crisis management in the Department of Passports and Immigration of the United Arab Emirates. The findings indicated that there was a statistically significant relationship between system quality, quality of services, information quality, and the speed of decision-making in computerized management information systems and crisis management in the Passports and Immigration Department of the UAE. The study recommended conducting similar studies in other places such as other emirates or neighbouring countries. The study also recommended conducting similar studies using a different methodology such as the qualitative approach, which may infer additional variables that may not have been included in the current research

Statistical performance of agglomerative hierarchical clustering technique via pairing of correlation-based distances and linkage methods

Agglomerative hierarchical clustering technique assists to group unknown objects into several clusters. The quality of clustering can be achieved when the clusters are internally homogeneous and externally heterogenous. However, the technique is sensitive to the choice of the distance measure and linkage method, particularly to the correlation-based distance because it is influenced by outliers. Choosing the wrong pairing may lead to the poor cluster formation and low clustering performance. Therefore, the main objective was to measure the statistical performance of agglomerative hierarchical clustering using four correlation-based distances and four linkage methods, tested through simulation study and real data application. The four correlation-based distances; Pearson, Spearman, Kendall’s Tau and Winsorized while the four linkage methods; Average, Ward’s, Complete and Single. The simulation study was conducted under various data conditions; number of variables, sample sizes, percentages of outliers, and data distribution to measure the performance using Cophenetic Correlation Coefficient (CCC). To validate the clustering model on real data, the Spearman-average algorithm was applied to cluster Juru river basin data based on five water quality parameters. The simulation study showed that the Spearman-average performed well under normal distribution and contaminated data, while the Winsorized-average performed well under Gamma distribution. Five tables of summary for choosing appropriate clustering algorithms according to data distribution were produced. The real data validation produced five clusters, with the CCC of 0.76 and the Calinski and Harabasz index of 26.879. In addition, the clustering model was also able to identify the time when the highest and lowest level of river contamination occurred. As a conclusion, the performance of clustering depends on the conditions of the data. Agglomerative hierarchical clustering is suitable to be performed when the number of variables is not more than 20 and the sample size smaller than 500

Identifying schematic, conversational and procedural representations of problem-solving language in debating discourse by a learner corpus analysis

Problem-solving communication is a crucial competency for university graduates. However, its relationship with debate participation has not been thoroughly examined. This study addresses the existing gap by examining parliamentary debate, a dynamic and increasingly popular impromptu format, to investigate its role in fostering problem-solving language. Using a corpus-based approach, the research analyzes the schematic, conversational, and procedural dimensions of problemsolving language as expressed in parliamentary debate discourse. A learner corpus comprising 751,328 tokens was compiled from 64 transcribed parliamentary debates sourced from the World Universities Debating Championships on YouTube. AntConc software was used to analyze key schematic features, including type token ratio, collocations, standardised frequencies, and concordance lines. The analysis revealed a strong presence of problem-solving language in the debating learner corpus, marked by a high type-token ratio and frequent use of keywords such as problem, need, issue, solution, solve, and fault(s) or drawback(s). These items showed notably high standardised frequencies, and concordance analysis indicated varied rhetorical functions within debate discourse. Genre analysis further identified structured problem-solving sequences typically following the stages of Situation, Problem, Response or Solution, and Evaluation. These rhetorical patterns highlight the conversational and interactive nature of parliamentary debate, which involves diverse argumentative roles such as propositions, oppositions, and Points of Information (POIs). The study provides corpus-based evidence of how problemsolving language is functionally deployed in debate, offering insights into the linguistic dynamics of argumentative communication and practical implications for education and debate training. The findings provide educators with genre prototypes for curriculum design, support corpus-driven analysis of argumentation, and assist debate participants in refining persuasive strategies for constructing effective problem-solving arguments. Ultimately, the study enhances the efficacy and engagement of parliamentary debate as a platform for developing critical communication competencies

The influence of perceived gender equality, perceived family support, and occupational stress on employee performance in it company Malaysia

This study investigates the influence of perceived gender equality, perceived family support, and occupational stress on employee performance within INSCALE Malaysia, a global technology services provider. Grounded in institutional theory, the Job Demands-Resources (JD-R) model, and social support theory, the research explores how psychosocial and organizational perceptions affect workforce outcomes. Using a quantitative research design, data were collected from the employees through structured questionnaires employing a simple random sampling technique. The study identifies significant correlations between perceived gender equality and employee performance, highlighting how gender-based disparities in career advancement and task delegation impact morale and output. Similarly, perceived family support emerged as a critical buffer against stress, promoting work-life integration and performance. Conversely, occupational stress arising from workload pressure and ambiguity negatively influenced cognitive and emotional well-being, impairing productivity. The findings offer theoretical contributions to human resource and organizational behavior literature by contextualizing Western performance models within Malaysia’s collectivist and multicultural work environment. Practically, the research underscores the need for inclusive HR policies, family-supportive initiatives, and stress-mitigation strategies tailored to Malaysia’s sociocultural realities. The study offers a performancecentric, perception-driven framework for enhancing productivity in knowledge-sector organizations operating in diverse setting

Making sense language of leadership and Pakistani identity through Mr. Imran Khan's discourse

Language serves as a primary medium of communication between the speaker and the listener. Furthermore, language and politics go hand in hand, as learning and comprehending political genre is to learn a language created for codifying, extending and transmitting political discourse in any text/talk. Language of political leaders might be one of the most challenging types of discourse, because it is usually characterised by the use of different techniques and strategies that allow political leaders to persuade people of their ideologies and thoughts for the construction of identities. In language of leadership, the strategy of convincing the audience to believe on what a leader says is very crucial. Therefore, balancing good persuasive strategy and speech delivery can make the political leaders produce an effective persuasive speech to maintain their identities. The present thesis examines the role of language of leadership and Pakistani identity in the spoken discourse of former Pakistan Prime Minister Mr. Imran Khan. Thus, this qualitative study explores the former Prime Minister of Pakistan, Mr. Imran Khan‘s language of leadership and Pakistani identity through his spoken discourse. More specifically, it reports the study which explores the language used during his leadership nationally and internationally. The data of the study were carefully collected from the content of the ten international interviews and ten international speeches of Mr. Imran and analysed based on the theoretical framework of Fairclough's three-dimensional model. Ten participants were selected for in-depth interviews to explore the opinions of Pakistani people on Mr. Imran Khan's language as a political leader. The findings indicate that Mr. Imran employed linguistic and rhetorical strategies in demonstrating his leadership in Pakistan and abroad as reflected in the spoken discourse. His persuasive and strong rhetoric clearly informed the world of his standpoints. He uses inclusive pronouns rather excessively to persuade the world communities on how to manage ecological and global issues. The study investigates not only the way identities are constructed and defended through language, but also their significance in shaping the professional image of Mr. Imran Khan. The study contributes to a deeper understanding of leadership language, Pakistani identity and its persuasiveness suggesting how they should be enhanced for better understanding particularly among future scriptwriters, learners of English language and political science student