Understanding Spatial Variability of Human Development Index in Aceh: A Geographically Weighted Regression Approach

Selvi Mardalena, Latifah Rahayu, Novi Reandy Sasmita, Raihan Hayati, Arhamun Nisa, Nurul Ummah, Septia Devi Prihastuti Yasmirullah

Abstract


The Human Development Index (HDI) is an important indicator in measuring people's quality of life, which includes education, health and economic dimensions. In Aceh Province, HDI achievements show inequality between regions, especially between coastal and inland areas. This study employs a quantitative spatial analysis to examine socio-economic determinants of HDI across districts using the Geographically Weighted Regression (GWR). The analysis utilized 2023 secondary data from the Central Bureau of Statistics (BPS), integrating HDI with key indicators of labor conditions, poverty, education, health, and regional economic performance. The global linear regression model was compared with GWR models using adaptive Gaussian and bisquare kernel weighting function, with model selection based on the Akaike Information Criterion (AIC). The results show that the GWR model with an Adaptive Gaussian Kernel weighting function outperformed the global regression model, indicating strong spatial non- stationarity in the relationships between HDI and its determinants. The average years of schooling, labor force participation rate, open unemployment rate, percentage of poverty, life expectancy, expenditure per capita, gross regional domestic product, and expected years of schooling have a significant effect on HDI in Aceh, but their contribution varies across districts. This study contributes to the literature by providing spatially explicit evidence to support region-based development policies, emphasizing the need for differentiated interventions to reduce interregional inequality and promote more equitable human development across Aceh Province.


Keywords


Aceh Province; Adaptive Gaussian Kernel; Geographically Weighted Regression (GWR); Human Development Index (HDI); Spatial Heterogeneity.

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DOI: https://doi.org/10.31764/jtam.v10i2.35734

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