Department Of Malaysia Research Articles

Leadership, Teamwork and Person-Organization Fit as Determinants of Job Satisfaction: A Case Survey among Public Sector Employees

Employee and job satisfaction has been major research in management studies throughout the world. It is the main concern for organizations to measure the performance of individuals by how they carry out their responsibilities in a manner that contributes to the achievement of the organization's goals and creates satisfaction feeling in their work. The purpose of this study is to examine the relationship between leadership, teamwork and person-organization fit on job satisfaction. Employees at Department of Statistics Malaysia were taken as the respondents in this study. Self-administered questionnaire used for collection of data. 80 questionnaires were distributed among above mentioned organization and 80 responds were return, so the response rate was 100%. The result concludes that there is significant relationship between the leadership and teamwork with job satisfaction meanwhile person-organization fit is not significant. Several recommendations were put forth in this study for the organization in promoting job satisfaction as well as recommendations for future research

A Two-Stage Feature Selection Method to Enhance Prediction of Daily PM2.5 Concentration Air Pollution

In recent decades, air pollution has negatively affected human health and the environment. One of the important features contributing to air pollution is called PM2.5. However, daily prediction of PM2.5 is still lacking, especially using feature selection infused into the model. Hence, the main objective of this research is to utilize the feature selection procedures by proposing two stages feature selection methods namely adjusted correlation sharing t-test (adjcorT) and radial basis function neural network (RBFNN) in identifying the important features. This consequently also helps enhance the prediction of daily PM2.5 concentrations. Secondary data were obtained from the Department of Environment Malaysia (DOE) from 2018 until 2022 that consists of 5 years of air pollutant daily data. The results found that adjcorT-RBFNN identified the NO2, PM2.5, PM10, CO, O3, wind speed and SO2 as important features. The finding revealed that the accuracy, sensitivity, specificity, precision, F1 score and AUROC value, for a day-ahead prediction in Shah Alam are 0.756, 0.801, 0.717, 0.717, 0.757, and 0.758 respectively. Additionally, the predicted model may serve as an instrument for an early warning system, providing local authorities with information on air quality for formulation of strategies of air quality improvement.

Personal Bankruptcy Prediction Using Logistic Regression Model

According to the Insolvency Department of Malaysia, as of December 2023, 233,483 Malaysians are currently involved in bankruptcy cases due to their defaults on hire purchase loans, credit card loans, personal loans, housing loans, and business loans. This is indeed a critical issue because the growing number of personal bankruptcy cases will hurt the Malaysian economy as well as society. From an individual's economic perspective, bankruptcy minimizes their chances of getting a job. Apart from that, their accounts will be frozen, they will lose control of their properties and assets, and they will not be allowed to start any business or be a part of any company's Board of Directors. Bankrupts also will be rejected from any loan application. This paper examines this problem by developing a personal bankruptcy prediction model using the logistic regression technique. This paper defines "bankrupt" as terminated members who failed to settle their loans. The sample comprised 24,546 cases with 17% settled cases and 83% terminated cases. The data included a dependent variable, i.e., bankruptcy status (Y=1(bankrupt), Y=0(non-bankrupt)), and 12 predictors. Upon completion, this paper succeeds in coming out with a reliable personal bankruptcy prediction model and significant variables of personal bankruptcy. The findings of this paper are very beneficial and significant to creditors, banks, the Malaysia Department of Insolvency, potential borrowers, members of AKPK, and society in general in raising awareness of personal bankruptcy risks and such information may help them to take preventive measures in minimizing the number of personal bankruptcy cases.

The Impact of Visual Digital Unit Exposure on Ocular Symptoms of Computer Vision Syndrome Among Selangor Office Workers

Objective: Computer Visual Syndrome (CVS) is a common condition characterized by a range of ocular symptoms resulting from excessive screen time. As visual digital unit (VDU) usage has skyrocketed across all age groups, CVS has become a prevalent issue in both personal and professional life. Therefore, this study aimed to investigate the association between the impact of VDU and ocular symptoms of CVS among office workers in Selangor. Material and Methods: In this cross-sectional study, 46 office workers completed a self-reported Computer Vision Syndrome (CVS) assessment using a questionnaire adapted from a previous study. The questionnaire includes 9 questions about ocular symptoms, rated on a 5-point scale: none, slight, moderate, severe, and very severe. Computer screen illumination was measured using a lux meter. To account for potential confounding factors, environmental conditions were also assessed. These included the number and type of light sources, window presence and size, window treatments, lighting fixture placement, and overall workspace cleanliness, following the guidelines on occupational safety and health for working with video display units by the Malaysia Department of Occupational Safety and Health.Results: Among all participants, the majority (93.5%) did not use anti-glare screen monitors and 20% had inadequate lighting with less than 450 lux. Of the respondents, 63% of the respondents reported experiencing eye strain and eye fatigue (60.9%) during work hours. Eye fatigue was the most commonly reported ocular symptom, with 24% of respondents experiencing it more than six times per week. Lighting reflector was found to be 3.5 times more prevalent to cause eye redness (odds ratio (OR)=3.50; 95% confidence interval (CI)=0.50–24.33). The likelihood of experiencing eye strain due to the absence of an anti-glare was 1.8 times higher and the absence of a lighting reflector increased the likelihood by 1.7 times. Conclusion: The alarmingly high prevalence of Computer Vision Syndrome (CVS) among office workers underscores the critical need for immediate and effective ergonomic interventions. This research is imperative to identify specific risk factors and develop targeted strategies to mitigate the detrimental effects of prolonged VDU use on ocular health.

Individual and contextual factors associated with measles infection in Malaysia: a multilevel analysis.

Despite effective vaccination strategies, measles remains a global public health challenge. The study explored individual and contextual factors associated with measles infection in Malaysia from 2018 to 2022, informing the development of targeted public health interventions. This cross-sectional study utilised data from the Ministry of Health, the Department of Statistics, and the Department of Environment Malaysia. Multilevel logistic regression analysis was employed to examine individual-level factors, including age, sex, ethnicity, nationality, contact history, travel history, and vaccination status. Concurrently, contextual factors were assessed, encompassing district-level determinants such as population density, median household income, urbanisation, the number of health and rural clinics, vaccination rates, PM2.5 levels, relative humidity, and temperature, to determine their impact on measles infection risk. Measles infection was significantly associated with various individual factors. These included age (adjusted odds ratio [aOR], 1.02; 95% confidence interval [CI], 1.02-1.03), ethnicity, non-Malaysian nationality (aOR, 34.53; 95% CI, 8.42-141.51), prior contact with a measles case (aOR, 2.36; 95% CI, 2.07-2.69), travel history (aOR, 2.30; 95% CI, 1.13-4.70), and vaccination status (aOR, 0.76; 95% CI, 0.72-0.79). Among contextual factors, urbanisation (aOR, 1.56; 95% CI, 1.16-2.10) and the number of clinics (aOR, 0.98; 95% CI, 0.97-0.99) were significant determinants. This multilevel logistic regression analysis illuminates the complexities of measles transmission, advocating public health interventions tailored to individual and contextual vulnerabilities. The findings highlight the need for a synergistic approach that combines vaccination campaigns, healthcare accessibility improvements, and socioeconomic interventions to effectively combat measles.

Exploring the impact of massification of higher education on the labour force participation and empowerment of Malaysian women

This paper aims to investigate the mismatch between the massification of higher education and the participation of women in the labour force in Malaysia. The objective is to statistically uncover the effect of educational attainment on the female labour force participation rate. The paper analyzed the data collected from various sources, like the World Bank, the World Economic Forum, and the Department of Statistics Malaysia. The paper employed various hypotheses tests, including the independent samples T-test, Mann-Whitney test, and Kruskal-Wallis test, to assess the relationship and determine whether to accept or reject the study hypotheses. The finding showed that females substantially outnumbered males among higher education’s graduates. Despite this improvement, women remain underrepresented in the labour force compared to the rate of their education attainment as well as that of men. The paper statistically rejects the notion that there is a positive linear connection between educating women and labour force participation. It is not all about educating women; decision-makers have to search for other factors that hinder women from fully participating in the labour force, particularly in the world of Muslim nations. The paper enriches the literature on gender parity and contributes to the ongoing debate about the effect of education on female labour force participation.

MODELLING DOMESTIC WATER DEMAND IN MALAYSIA TO IDENTIFY INFLUENCING FACTORS: A COMPARATIVE ANALYSIS

Water crises are often experienced by many developing countries worldwide. Predicting future domestic water demand and identifying the influential factors are vital to managing water supply effectively. This study aims to determine the best predictive models among Multiple Linear Regression (MLR), Multi-layer Perceptron (MLP), and Radial Basis Function (RBF) Neural Networks as well as to identify the significant influential factors towards domestic water demand. Based on the yearly records from 2000 to 2018 obtained from the Malaysian Water Association, the Department of Environment, and the Department of Statistics Malaysia the analysis results indicate an increasing pattern of domestic water in Malaysia with the demand for non-domestic water twice lower than domestic water. Based on RMSE and R-squared, Multi-layer Perceptron is the best model for predicting domestic water demand. The MLR model shows that the two most significant influential factors towards domestic water demand are price and design capacity, with negative and positive relationships. The results describe that an increase in price affects a decrease in water demand, while an increase in design capacity will reduce the water demand. The findings suggest that the water utilities in Malaysia should focus more on these identified factors.

Causes and Trends of Motorcycle Accidents

Road safety has long been considered as one ofthe social responsibilities to the Malaysian Government. Inthe visibility of this responsibilities, multiple bodies concernon road safety has been formed within the governmentdepartments, private agencies, and voluntary organizations.The current study was carried out to understand the recenttrend and statistics of road motorcycles in Kajang,Malaysia. The statistics for road accidents and the relatedcasualties in Malaysia from 2005 to 2008 was obtained fromthe Bukit Aman Police Headquarters. The statistics ofregistered motor vehicles in Malaysia will be provided byRoad Transport Department of Malaysia. Data will beanalyzed using SPSS software. Descriptive and hypothesistesting techniques were used to obtain the results based onthe stated objectives of the study. From the crash statistics,it can be revealed that Kajang has a relatively higherincidence of casualties (dead, seriously injured and lightlyinjured). In addition, the results show that the young ridersof motorcycles among the age of 16 to 20 years from themajority of those who die in motorcycles accidents.Moreover, it is recognized that the considerable percentageof the motorcyclists and the pillion riders did not wearsafety helmets when they were traveling on the roadsnetwork. The Malaysian government has to organize manymotorcycle safety campaigns in the coming few years.

Effect of activated carbon compaction on water filtration efficiency

Water contamination in rural Malaysian areas, mainly caused by logging activities leading to soil erosion and river pollution, presents a significant threat to water supplies. In response, a specialized activated carbon water filtering device was developed to target the absorption of organic molecules. The impact of compaction of activated carbon on water filtering efficiency was evaluated. Testing both compacted and uncompacted activated carbon filters with contaminated river water, the study utilized the Malaysia Department of Environment’s (DOE) water quality index (WQI) to assess filter effectiveness. The results revealed that water filtered through compacted activated carbon was clearer and less yellowish compared to the uncompacted counterpart. Moreover, the compacted filter showed higher dissolved oxygen levels, lower ammoniacal nitrogen levels, and a lower pH, resulting in a significantly higher WQI score of 80.4 compared to 78.8 for the uncompacted filter. Further analysis via an adsorption isotherm test demonstrated the superior ability of compacted activated carbon to absorb acetic acid, as evidenced by higher lines in the Freundlich isotherm model graphs. These findings emphasize the efficacy of compacted activated carbon in water filtration, advocating for its integration into filter construction to enhance water quality in rural regions.

Benefits and Challenges of Digital Audit Implementation in the Malaysian Public Sector: Evidence from the Accountant General's Department of Malaysia

Purpose: The current study aims to investigate the important benefits or advantages of digital audit implementation perceived by the internal auditors of the Accountant General’s Department of Malaysia (AGD), and examine the significant challenges faced by the AGD auditors in implementing digital audit. Design/ Methodology/ Approach: A focus group discussion was conducted with AGD officers involved in digital audit implementation and a questionnaire survey was distributed to the AGD auditors to achieve the research objectives. All 124 auditors responded and returned the completed questionnaire. Thematic analysis was performed on the transcription of the focus group discussion while descriptive statistics of mean scores, standard deviations, and mean score ranking were utilised to analyse the questionnaire data. Findings: The top five ranked benefits of digital audit implementation perceived by the respondents were improving the quality of audit report, increasing the efficiency of audit, assisting auditors in identifying material misstatements, improving the quality of the audit processes and enhancing audit effectiveness. The top three challenges were requiring additional education and training to acquire the necessary digital skills, high implementation costs and the risk of data security (leakage) and confidentiality. Originality/ Value: The present study contributes to the existing limited empirical evidence on the fundamental advantages and challenges of digital audit implementation despite various conceptual discussions on the two implementation aspects.

Benefits and Challenges of Digital Audit Implementation in the Malaysian Public Sector: Evidence from the Accountant General's Department of Malaysia

Benefits and Challenges of Digital Audit Implementation in the Malaysian Public Sector: Evidence from the Accountant General's Department of Malaysia

Issues and Challenges in Accounting for Infrastructure Assets in the Malaysian Government and the Way Forward

Purpose: The current study seeks to examine the issues and challenges encountered by the Malaysian government accounting staff in recognising and measuring infrastructure assets. Additionally, recommendations for further actions by the Accountant General’s Department of Malaysia (AGD) and suggestions for future research were delineated. Design/ Methodology/ Approach: This study employed a qualitative approach through archival search and semi-structured interviews. Interviews were conducted with 52 government staff representing 10 ministries, three state governments, and three local governments. The respondents were selected through purposive sampling and snowballing techniques. Findings: Accounting for infrastructure assets in Malaysia adheres to Malaysian Public Sector Accounting Standards (MPSAS) 17 and several other government guidelines. Several ministries experienced difficulties in identifying the infrastructure assets due to lack of clarity in the definition and flexibility of the current accounting standards and guidelines. Moreover, the unique features of infrastructure assets, namely a long useful life and being part of an asset system or network, led to challenges in recognition and measurement. Practical Implications: The findings provided several practical recommendations for the AGD’s understanding of the issues and challenges encountered by the accounting staff, which would assist in formulating policies and guidelines for infrastructure asset accounting. Originality/ Value: The present study significantly contributed to the existing body of literature on accounting for infrastructure assets which remains scarce in Malaysia.

Issues and Challenges in Accounting for Infrastructure Assets in the Malaysian Government and the Way Forward

Purpose: The current study seeks to examine the issues and challenges encountered by the Malaysian government accounting staff in recognising and measuring infrastructure assets. Additionally, recommendations for further actions by the Accountant General’s Department of Malaysia (AGD) and suggestions for future research were delineated. Design/ Methodology/ Approach: This study employed a qualitative approach through archival search and semi-structured interviews. Interviews were conducted with 52 government staff representing 10 ministries, three state governments, and three local governments. The respondents were selected through purposive sampling and snowballing techniques. Findings: Accounting for infrastructure assets in Malaysia adheres to Malaysian Public Sector Accounting Standards (MPSAS) 17 and several other government guidelines. Several ministries experienced difficulties in identifying the infrastructure assets due to lack of clarity in the definition and flexibility of the current accounting standards and guidelines. Moreover, the unique features of infrastructure assets, namely a long useful life and being part of an asset system or network, led to challenges in recognition and measurement. Practical Implications: The findings provided several practical recommendations for the AGD’s understanding of the issues and challenges encountered by the accounting staff, which would assist in formulating policies and guidelines for infrastructure asset accounting. Originality/ Value: The present study significantly contributed to the existing body of literature on accounting for infrastructure assets which remains scarce in Malaysia. Keywords: Infrastructure assets, recognition, measurement, IPSAS 17, MPSAS 17.

Statistical Analysis of Occupational Fatal Accidents for Risk Assessment

Abstract According to Malaysia's Department of Occupational Safety and Health (DOSH), workplace accidents have increased dramatically as the country's economy has grown rapidly. The purpose of this study is to identify the trends that lead to fatal workplace accidents in Malaysia. This study investigated 505 fatal accident instances from fifteen industries, using both qualitative and quantitative methodologies. The DOSH discovered and reported these fatalities (2010-2020). Data was organized and coded, then analyzed using Spearman's rank order correlation, frequency analysis, Eta squared, Cramer's V, and Chi-square. Moreover, neurolinguistic programming was used to generate the word cloud and sentiment analysis. Furthermore, light gradient-boosting machine learning was used to better understand the causes of fatalities. The outcomes indicated that fatal falls from heights were the leading cause of fatal accidents (32%). General laborers were the most susceptible to fatal accidents (60%). Contract workers were more likely to die in construction accidents (64%). The findings of this study gave useful insights into workplace fatal accident trends and preventive measures throughout sectors.

Risk Exposure of Coastal Inundation from Storm Surge in the Northern part of Malaysian Borneo

Abstract Coastal communities heavily rely on marine resources for their livelihoods. The rising occurrence of extreme weather events have affected both the coastal ecosystems and socio-economic activities. One of the most prevalent extreme events in Malaysia is the storm surge. This study aims to assess the extent of coastal inundation based on three storm surge scenarios (categories by Meteorological Department of Malaysia) and to determine the risk exposure ranking of nine study sites. Field trips and interviews were conducted from March 2020 to March 2023 in Kudat located at the northern part of Malaysian Borneo. One hundred respondents were surveyed using semi-structured open-ended questionnaires to evaluate the risk exposure of coastal inundation caused by storm surges. The findings revealed that Category 1 flooded certain sites of west (Kimihang) and east (Tajau Laut) sides of Kudat. The Category 2 have significantly flooded one site in the west side (Simpang Mengayau) of Kudat. While, for Category 3 of coastal inundation affected two sites in east sides of Kudat (Tanjong Kapor and Landung Ayang). These two sites in east sides of Kudat also experienced a high level of risk exposure due to the lack of diverse coastal ecosystems and high population density. While three sites in west side of Kudat (Kimihang, Kelambu and Simpang Mengayau) faced significant impacts on social services, particularly within the tourism sector. Despite relying on multiple livelihoods, these sites were susceptible to storm surges. Additionally, the increasing development for tourism purposes posed a threat to the richness of the ecosystem. This study suggests that certain sites in east side of Kudat (Tanjong Kapor and Landung Ayang) are highly exposed to risk and require measures for adaptation and mitigation.

High-Resolution Downscaling with Interpretable Relevant Vector Machine: Rainfall Prediction for Case Study in Selangor

Due to the discrepancy in resolution between existing global climate model output and the resolution required by decision-makers, there is a persistent need for climate downscaling. We conducted a study to determine the effectiveness of Relevant Vector Machine (RVM), one of the machine learning approaches, in outperforming existing statistical methods in downscaling historical rainfall data in the complex terrain of Selangor, Malaysia. While machine learning eliminates the requirement for manual feature selection when extracting significant information from predictor fields, considering multiple pivotal factors is essential. These factors include identifying relevant atmospheric features contributing to rainfall, addressing missing data, and developing a significant model to predict daily rainfall intensity using appropriate machine-learning techniques. The Principal Component Analysis (PCA) technique was employed to choose relevant environmental variables as input for the machine learning model, and various imputation methods were utilized to manage missing data, such as mean imputation and the KNN algorithm. To assess the performance of the RVM-based rainfall model, we collected a dataset from the Department of Irrigation and Drainage Malaysia. We used Nash-Sutcliffe Efficiency (NSE) and Root Mean Square Error (RMSE) as evaluation metrics. This study concluded that Relevance Vector Machine (RVM) models are suitable for forecasting future rainfall since they can support large rainfall extremes and generate reliable daily rainfall estimates based on rainfall extremes. In this study, the RVM model was employed to determine a predictive association between predictand variables and predictors.

Firefighting Water Tanker Commuting Accident: Case report on why it happened and how to manage

Road traffic accidents represent a significant global public health concern, and Malaysia is no exception. Within the Fire and Rescue Department of Malaysia (FRDM), similar issues have had detrimental impacts on health, financial loss, and service disruptions from 2016 to 2021. These challenges were highlighted by a recent accident involving a water tanker during a road test, described in this study according to qualitative data from the FRDM accident investigation report. The investigation revealed that human factor, as the active failure, was the primary cause of the accident. Response errors stem from a cascade of latent conditions initiated by inadequate resource management (i.e. provision of training and budget allocation). To address these challenges, the FRDM should adopt a comprehensive approach to address both latent conditions and active failures. This comprehensive approach ensures that both immediate concerns and root causes are addressed, leading to sustained improvements in safety and operational performance.

Financial Education in Malaysian Primary Schools Curriculum

Statistics from the Insolvency Department of Malaysia (IDM), (2020) have stated that a total of 84,805 individuals have been declared bankrupt in the five years from 2015 to December 2019. Malaysian Ministry of Education (MOE) is responsible for developing young people who are financially literate and smart in managing personal finances through the Strategy initiative National Financial Literacy 2019-2023. In line with efforts to instill good values from a young age, MOE has integrated elements of Financial Education in the school curriculum gradually, systematically, and comprehensively since 2014. Financial Education contents were explicitly written in primary school Mathematics Standard-Based Curriculum and Assessment Document (DSKP).

Predicting air quality trends in Malaysia’s largest cities: the role of urban population dynamics and COVID-19 effects

This paper aims to explore the relationship between the Air Quality Index (AQI), COVID-19 incidence rates, and population density within Malaysia’s ten most populous cities from January 2018 to December 2021. Data were sourced from the Department of Statistics Malaysia, the World Air Quality Index Project, and Our World in Statistics. The methodology integrated population-based city classification and AQI assessment, cluster analysis through SPSS, and Generalized Additive Mixed Model (GAMM) analysis using R Studio despite encountering a data gap in AQI for five months in 2019. Cities were organized into three clusters based on their AQI: Cluster One included Ipoh, Penang, Kuala Lumpur, and Melaka, Cluster Two comprised Kuantan, Seremban, Johor Bahru, and Kota Bharu, Cluster Three featured Kota Kinabalu and Kuching. GAMM analysis revealed prediction accuracies for AQI variations of 58%, 60%, and 41% for the respective clusters, indicating a notable impact of population density on air quality. AQI variations remained unaffected by COVID-19, with a forecasted improvement in air quality across all clusters. The paper presents novel insights into the negligible impact of COVID-19 on AQI variations and underscores the predictive power of population dynamics on urban air quality, offering valuable perspectives for environmental and urban planning.

From Classrooms to Economies: Examining the Educational Achievement-Economic Development Nexus

Abstract Each states play pivotal roles in contributing to the economic performance of the nation. They have their own unique economic strengths, resources, and industries that contribute to the overall economic development. Terengganu, an east coast state in Malaysia has historically faced economic challenges, marked by a lag in development compared to other regions. The fundamental problem addressed is the potential correlation between educational attainment and the region’s economic growth, aiming to understand how advancements in education might serve as a catalyst for economic progress. The objective of this research is to empirically analyze the impact of educational achievement on the economic development in Terengganu. Utilizing secondary data sourced from the Department of Statistics Malaysia and Economy Planning Unit Terengganu spanning from 2006 to 2022, Autoregressive Distributed Lag (ARDL) model has been employed to estimate and understand the relationship between educational attainment and economic development. The findings suggested that educational achievement plays positive impact in heightening the economic development within the region. Education contributes to the development of human capital, fostering a skilled and knowledgeable populace capable of engaging in diverse economic activities. This, in turn, attracts investments and facilitates the emergence of industries and sectors that rely on a knowledgeable and skilled labour force. This study would provide valuable insights for policymakers and academicians to formulate targeted policies and initiatives, ultimately enhancing the economic development of the states, thus contribute to a prosperous Malaysia.