Spatial Patterns of Income Inequality and Poverty in Central Java Province: A Moran's I and LISA Approach

Abstract

Income inequality and poverty remain regional development challenges, as they exhibit distinct spatial characteristics across regions. This study aims to analyze the distribution and spatial autocorrelation of income inequality and poverty in 35 districts/cities in Central Java Province, Indonesia, in 2025. Secondary Data on the Gini ratio and the percentage of the poor population were obtained from the Indonesian Statistics. Spatial analysis was done using thematic mapping, Queen Contiguity spatial weight matrix, Global Moran's I, and Local Indicators of Spatial Association (LISA). The results showed that the Gini ratio had a relatively weak positive spatial autocorrelation (Moran's I = 0.181; z = 1.855; pseudo p = 0.043), while poverty also showed a slightly higher positive spatial autocorrelation but remained relatively weak (Moran's I = 0.237; z = 2.246; pseudo p = 0.021). LISA's analysis shows that there are low–Low Gini ratio clusters in Jepara, Pati, and Kudus, while high–High poverty clusters are found in Banjarnegara, Banyumas, Cilacap, Purbalingga, Purworejo, and Kebumen. These findings suggest that the spatial pattern of poverty is broader than income inequality, while the two indicators represent different dimensions of well-being. The results of the study confirmed the importance of spatial perspective in formulating more contextual regional development policies.