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The complexity of regional disparity has encouraged viewing this issue from various perspectives, one of which is the role of physical geography in disparity. On Java Island, an observation on the role of geographical aspect is needed due to the spatial sturdiness of disparity. This study aims to provide quantitative proof that differences in the physical geography of Java’s regions account for the persistent regional disparity. We applied two approaches namely correlation and typology, employing data of physical geographical attributes and development level. The methods used were correlation analysis, factor analysis, cluster analysis, and one-way ANOVA. Based on the correlation approach, we found the association of regional development level with terrain ruggedness, soil parent materials, sea depth, elevation, and precipitation. Then, based on endowment-based typology approach, Java’s regions could be grouped into lowland, volcanic, old volcanic, and calcareous dry regions. The two latter performed poorly in all socio-economic indicators examined.

Although uneven regional development has long been an issue in Java, most parts of the territory experienced an increased level of development over the last two decades. Due to the variance in local background and spatial heterogeneity, the driving factors of the development level should, theoretically, vary over space. Therefore, in this study, we aim to investigate the local factors that influence the development level of Java’s regions. We used the spatiotemporal pattern analysis, ordinary least squares (OLS) regression, and geographically weighted regression (GWR), utilizing the regional development index as the predicted variable, and the social level, economy, infrastructure, land use, and environmental barriers as predictors. As per our results, it was found that the level of development in Java has improved over the past two decades. Metropolitan areas continued to lead this improvement. All the predictors that we examined significantly affected regional development. However, the spatial pattern of the local regression coefficients of Human Development Index (HDI), landslide, paddy conversion, and crime shifted due to changes in the spatial concentration of development activities.