The level of human quality development between regions or countries can be measured using the Human Development Index (HDI) value. The higher the value of the HDI, the better the quality of human development in the region. Some variables affect the value of the HDI. This study will test six independent variables using the Geographically Weighted Panel Regression (GWPR) method. This GWPR method combines panel data regression with the Geographically Weighted Regression (GWR) method. This GWPR method combines the dimensions of location and time to determine the effect of the independent variable on the dependent variable. Therefore, the purpose of this study is to see which variables have a significant effect on the value of the HDI in Papua Province. By using panel data regression, the best model that can be formed is the Fixed Effect Model (FEM). However, the FEM model that was formed did not meet the heteroscedasticity assumption test on the residuals, so further modeling was carried out using the GWPR model. GWPR modeling on this data uses a kernel weighting function, whereas previously, data transformation was carried out by the concept of the FEM model. The GWPR model with the best kernel weighting function is fixed exponential. In selecting the best model based on the coefficient of determination , the GWPR model is better than the FEM model. Regarding the significance of model parameters, nine groups of districts/cities based on independent variables significantly affect the HDI. In all districts/cities of Papua Province, the per capita expenditure variable significantly affects the HDI's value.
Mahmudi et al. (Thu,) studied this question.
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