Modeling Human Development Index Determinants in Central Java: A Comparison of Gamma GLM and Linear Regression
DOI:
https://doi.org/10.24252/msa.v14i2.65279Keywords:
Central Java, Gamma GLM, Human Development Index, Multiple Linear RegressionAbstract
The Human Development Index (HDI) is a composite indicator widely used to evaluate human The Human Development Index (HDI) is a composite indicator commonly used to assess regional human development outcomes based on health, education, and living standards. This study aims to identify the determinants of HDI across regencies and cities in Central Java Province in 2024 and to compare the performance of Multiple Linear Regression and the Gamma Generalized Linear Model (GLM) in modeling HDI. The analysis utilizes cross-sectional secondary data from 35 regencies/cities obtained from Statistics Indonesia (BPS). Multicollinearity was assessed using the Variance Inflation Factor (VIF), and model performance was evaluated through parameter significance and the Akaike Information Criterion (AIC). The results reveal substantial interregional disparities, with an average HDI of 75.54 and a variance of 14.05. Expected Years of Schooling shows the strongest positive and highly significant effect on HDI in both models (p < 0.001), followed by Life Expectancy at Birth and BPJS health insurance participation. In contrast, poverty rate and health complaints exert significant negative effects. The Gamma GLM yields a lower AIC value (93.82) than the multiple linear regression model, indicating superior goodness of fit and greater sensitivity to health-related factors. These findings underscore the central role of education and health in human development and support the use of Gamma GLM as a more appropriate modeling approach for HDI.
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