Geographically Weighted Regression (GWR) Modeling in Identifying Factors Affecting the Gender Empowerment Index in Indonesia - Meliyana, Sitti Masyitah; Rahman, Abdul; Ahmar, Ansari Saleh (PT Mattawang Mediatama Solution, 2025)
This study aims to analyze the factors influencing the Gender Empowerment Index (GEI) in Indonesia using the Geographically Weighted Regression (GWR) method. The variables used in this study include the proportion of women in managerial positions, women’s income contribution, the proportion of professional workers, reported health complaints, and the proportion of women in parliament. The findings indicate that, among the five independent variables examined, only two variables significantly affect the dependent variable: the proportion of women in managerial positions (X1) and the percentage of women reporting health complaints (X5). This is evidenced by their respective probability values (Pr(>F)) of 0.0045 and 0.0128, which are below the 0.05 significance threshold. This implies that X1 and X5 have a statistically significant influence in the model. The GWR model was found to be the most suitable compared to other models, with an AIC value of 186.72 and an R² of 92.03%, indicating superior model performance in capturing spatial and non-spatial effects across regions.