A prospective study of dengue infection in Malaysia: A structural equation modeling approach

Background: Dengue fever has been a major health threat to Malaysia over one century since 1902. This situation is getting worse every year so that the government has taken an affirmative action to tackle this particular issue. The purpose of this study was to investigate the effect of government support, climate changes, public attitude, population growth, and environment on dengue infection. Also, this study considered the environment as a mediator construct as the past literature revealed its role in dengue infection model. Methods: In order to identify the relationship between exogenous and endogenous constructs, structural equation modeling (SEM) was used. Also, in order to identify the factors affecting dengue infection, measurement and structural model evaluation were applied. Using stratified sampling method, 670 questionnaires were distributed among prospective respondents from eastern region, but in turn, only 505 cases could be used after data cleaning process. Results: Considering environment factor as a mediator, the results show that public attitude and population growth have a significant impact on the environment, while government support, public attitude, and environment factors have a significant impact on dengue infection. Population growth was the most important factor affecting dengue fever. Conclusion: According to the results, dengue fever that emanating from four exogenous and one mediator constructs are adequate to discuss on respondent perception of dengue fever in Malaysia. Keywords: Dengue infection, Population growth, Malaysia, Government, Surveys and questionnaire

PREDICTION OF MALAYSIAN WOMEN DIVORCE USING MACHINE LEARNING TECHNIQUES

This paper discusses the performance of three machine learning techniques namely Decision Tree, Logistic Regression and Artificial Neural Network for predicting divorce among Malaysian women. Secondary data were obtained from the Fifth Malaysia Population and Family Survey (MPFS-5) conducted by the National Population and Family Development Board (LPPKN). The total number of instances in the dataset was 7,644 ever married Malaysian women aged 15 to 59 years old. Divorce is currently a serious problem among the Malaysian community due to various reasons. In 2019, the divorce rate in Malaysia rose by 12% from the previous year. During the first three months of the Movement Control Order (MCO), i.e. from March 18 to June 18, 2020, the Syariah Court of Malaysia recorded 6,569 divorce cases. Worse, a total of 90,766 divorce cases were recorded from January to October 2020. Six predictive models were used for comparison, namely Decision Tree (C5.0 and CHAID), Logistic Regression (Forward Stepwise and Backward Stepwise), and Artificial Neural Network (Multi-Layer Perceptron and Radial Basis Function). Among the six predictive methods, the Decision Tree model (C5.0) was found to be the best model in classifying divorce among Malaysian women. The accuracy of the C5.0 model was 77.96% followed by the Artificial Neural Network (Multi-Layer Perceptron) and Logistic Regression (Forward Stepwise) model (74.68% and 67.89%, respectively). The order of important predictors in predicting divorce among Malaysian women is the wives’ employment status (0.1531) followed by the husbands’ employment status (0.1396), type of marriage (0.1327), race/ethnicity (0.1327), distant relationship (0.1212), the wives’ qualification level (0.1115), age group (0.1053) and religion (0.0998)