Abstract

This article aims to examine the factors that influence income inequality by considering the spatial aspect. This article will compare the performance of the global regression model with the Geographically Weighted Regression (GWR) model in measuring the influence of socioeconomic factors on income inequality in East Java. The observation locations are 38 regencies/cities in East Java using data from the Statistics Indonesia of East Java Province database in 2021. The results show that the data used in this study contains spatial effects and spatial modelling with the GWR method using the gaussian adaptive kernel. The performance of the GWR model is better than the global linear regression model, the GWR model can explain the diversity of income inequality cases by 66.62% with an AIC value of 75.41. The two most dominant economic factors influence income inequality in all regencies/cities of East Java Province, while only 20 areas are affected by the percentage of the working-age population with higher education, and 21 areas are affected by the number of villages by the incidence of the crime factor