What predicts job satisfaction in Malaysia?

The purpose of this study is to address the gaps in the literature and to examine the predictors of job satisfaction. In this study, the hypothesized predictors influencing one’s job satisfaction are a) gender, b) age, c) level of education, d) salary, e) role in the job, and f) years of working in the organization. This study used Minnesota Satisfaction Questionnaire (MSQ) as a data gathering tool. The questionnaires were administered to 89 male respondents, and 121 female respondents. For data analysis, Statistical Package for Social Sciences (SPSS) was employed. In addition to conducting a multiple regression analysis (MRA), descriptive statistical analysis was also carried out as part of the data analysis. Of all the predictors studied, results indicated gender as the only significant predictor of one’s job satisfaction. Several recommendations for future studies were also listed

On A Comparison between Two Measures of Spatial Association

Two measures of spatial association between two variables were used by many researchers. These are the Wartenberg (1985) and Lee (2001) measures. Based on simulation for lattice data, the sensitivity of both measures was studied and compared with different choices of spatial structures, spatial weights and sample sizes using bias and mean square error. Different scenarios are used in terms of assumed numbers and sample sizes. Moran’s I is used to examine the spatial autocorrelation of such a variable with itself. Both the Wartenberg and Lee measures are found to be sensitive, however, Wartenberg’s measure is found to be somewhat better than Lee’s measure because it is slightly more sensitive when sample size is small

Bayesian inference for linear regression under alpha-skew-normal prior [Pentaabiran Bayesian untuk Model Regresi Linear Prior Normal-Pencong-Alfa]

A study on Bayesian inference for the linear regression model is carried out in the case when the prior distribution for the regression parameters is assumed to follow the alpha-skew-normal distribution. The posterior distribution and its associated full conditional distributions are derived. Then, the Bayesian point estimates and credible intervals for the regression parameters are determined based on a simulation study using the Markov chain Monte Carlo method. The parameter estimates and intervals obtained are compared with their counterparts when the prior distributions are assumed either normal or non-informative. In addition, the findings are applied to Scottish hills races data. It appears that when the data are skewed, the alpha-skew-normal prior contributes to a more precise estimate of the regression parameters as opposed to the other two priors. - 2019 Penerbit Universiti Kebangsaan Malaysia. All rights reserved.Scopu

Measuring income inequality in Malaysia based on household income survey

Several policies have been introduced by Malaysian government with the aim of reducing the income inequality among the citizens. This study examines the changes in income inequality based on three different indices, which are Gini, Atkinson and generalized entropy using the household incomes data available from the surveys conducted in 2007, 2009, 2012 and 2014. Modification for each index is employed by taking sample weights into account for better measurement. Lorenz curves are fitted to the data to describe how the incomes of different household income groups are distributed over the time period. All the indices show a decreasing trend from 2007 to 2014, indicating an overall improvement of income distribution. The proportions of income earned by the low income groups have increased from 14.25% in 2007 to 16.28% in 2014 after taking economic pie from the higher income group while the middle class remains unchanged

A Preliminary Study of the Influence of Social Media Engagement on Information Seeking Behavior among the Secondary School Students

The aim of conducting this research is to examine the influence of social media engagement on information-seeking behavior. There is lack of concern about generalizability and implementation towards emphasizing the effects of social media engagement on information-seeking behavior in Malaysia. A close-ended questionnaire was distributed to the students to conduct the data collection for this research. The data was collected from students and was analyzed using SPSS version 26. Findings show that two hypotheses were accepted; Novelty and Perceived Usability have a positive and significant relationship between information-seeking behavior, while Focus Attention and aesthetics were found insignificant for information-seeking behavior. Keywords: Social media, information-seeking behavior, Social media engagement,  aesthetic, education eISSN: 2398-4287 © 2022. The Authors. Published for AMER ABRA cE-Bs by E-International Publishing House, Ltd., UK. This is an open-access article under the CC  BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under the responsibility of AMER (Association of Malaysian Environment-Behavior Researchers), ABRA (Association of Behavioral Researchers on Asians), and cE-Bs (Centre for Environment-Behavior Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia

Comparison of water level measurement performance for two different types of diaphragm using fiber bragg grating based optical sensors

A sensor head incorporating a diaphragm was designed and fabricated for water level measurement. It operates in the range of 0-70 cm column height, equivalent to a pressure in atmospheric pressure of 0-6. 86 kPa. The fiber Bragg grating (FBG) was attached on the two types of diaphragm to detect the change in the hydrostatic pressure caused by water at different levels. The diaphragms performance by comparing the sensitivity in within the mentioned range. Optical spectrum analyzer (OSA) was used to record the shift in the Bragg wavelength λB at different water level. The sensitivity of water level measurement using a silicone rubber diaphragm found to be 9.81 pm/cm for 70 cm in water level, while the sensitivity for polymer plastic diaphragm found to be 2 pm/cm at the same leve

Water level measurement via polymer-fiber Bragg grating sensor

In this paper, a new design of sensor head to monitor water level inside the tank based on fiber Bragg grating (FBG) was demonstrated. The sensor head consisted of an FBG placed under a very thin polymer plastic sheet layer. This sensor head acts as a sensitive diaphragm to sense water level based on hydrostatic pressure caused by the liquid weight. The hydrostatic pressure imposed on the sensor head produced strain in the embedded FBG, which caused a shift in Bragg wavelength detected by the optical spectrum analyzer. A calibration curve to relate liquid level and shift in the Bragg wavelength was constructed. A linear relationship between the shift in Bragg wavelength and the water level up to 70 cm height with a sensitivity of 2 pm/cm is achieved in this work

ORDINAL REGRESSION FOR MODELLING THE FAMILY WELL-BEING AMONG THE MALAYSIANS

Background and Purpose: Understanding factors which affect the level of family well-being is important as it contributes to effective decision making among the policymakers to improve the family lives as well as to strengthen the family institution. Accordingly, this line of research is gaining attention. This study develops an ordinal regression model which identifies demographic, economic and social factors that are significant in explaining the status of family well-being.    Methodology: Data involving 2,808 respondents from a nationwide survey conducted by the National Population and Family Development Board of Malaysia in 2011 were used in this study. Ordinal regression model was implemented to describe the three levels of family well-being.   Findings: The national survey reported that high level of family well-being was experienced by 76.3 per cent of the respondents, followed by moderate (18.4%) and low (5.3%). The fitted ordinal regression model found that ethnic background, family relationship, community relationship, health and safety levels, economic situation of the family, religious practice, housing, and environment are significantly related to family well-being. Meanwhile, it was found that the level of income is not a significant factor in determining the level of family well-being.     Contributions: There are a limited number of studies on the application of ordinal regression for modelling the level of family well-being, particularly with covariates involving the demographic and social characteristics of the respondents. This study fills in the gap in the literature where the ordinal regression model provides useful information for policymakers to enhance the status of family well-being in Malaysia via various policy initiatives.   Keywords: Family well-being, Ordinal Regression Model, ordinal data, Proportional Odds Model.   Cite as: Muhammad Sapri, N. A., Ibrahim, K., Abu Bakar, M. A., & Mohd Ariff, N. (2021). Ordinal regression for modelling the family well-being among the Malaysians.  Journal of Nusantara Studies, 6(2), 424-447. http://dx.doi.org/10.24200/jonus.vol6iss2pp424-44

The extra zeros in traffic accident data: a study on the mixture of discrete distributions

The presence of extra zeros is commonly observed in traffic accident count data. Past research opt to the zero altered models and explain that the zeros are sourced from under reporting situation. However, there is also an argument against this statement since the zeros could be sourced from Poisson trial process. Motivated by the argument, we explore the possibility of mixing several discrete distributions that can contribute to the presence of extra zeros. Four simulation studies were conducted based on two accident scenarios and two discrete distributions: Poisson and negative binomial; by considering six combinations of proportion values correspond to low, moderate and high mean values in the distribution. The results of the simulation studies concur with the claim as the presence of extra zeros is detected in most cases of mixed Poisson and mixed negative binomial data. Data sets that are dominated by Poisson (or negative binomial) with low mean show an apparent existence of extra zeros although the sample size is only 30. An illustration using a real data set concur the same findings. Hence, it is essential to consider the mixed discrete distributions as potential distributions when dealing with count data with extra zeros. This study contributes on creating awareness of the possible alternative distributions for count data with extra zeros especially in traffic accident applications

Time series clustering of Malaysia Air quality time series data

Air quality is often associated with the area location and activities where air quality in cities is usually more polluted than in rural areas. This study aims to study the pattern of time series data from air quality stations by performing cluster analysis of air quality station based on the particulate matter 10 micrometres or less in diameter (PM10) and particulate matter 2.5 micrometres or less in diameter (PM2.5) time series data. The clusters obtained from the cluster analysis were compared with the station area category and station location. This study which uses air quality data obtained from the Department of Environment, Malaysia from 5 July 2017 until 30 June 2019, shows five types of air quality patterns in Malaysia. The results also show that none of the clusters is dominated by any station's category. Therefore, it is less appropriate to relate the air quality patterns and the station area category. However, the results show that air quality patterns were related to the station's location, where nearby stations have similar air quality patterns