<![CDATA[Poverty in Indonesia remains a complex development challenge and tends to exhibit spatial clustering rather than a random distribution. In West Java Province, high population density and disparities in poverty levels across districts and cities underscore the importance of adopting a spatial perspective in poverty analysis. This study aims to identify global and local spatial dependence of poverty and to map poverty clusters in West Java Province. The analysis uses secondary data on district/city-level poverty rates in 2024 obtained from Central Bureau of Statistics (BPS). Spatial analysis is conducted using Global Moran’s I to assess overall spatial autocorrelation and Local Indicators of Spatial Association (LISA) to identify local clusters and spatial outliers, employing a queen contiguity spatial weight matrix. The results indicate a significant positive spatial autocorrelation, confirming the existence of spatial clusters of both high and low poverty across the province. These findings highlight the strong spatial dimension of poverty in West Java and suggest that poverty alleviation policies should be designed using a region-based and spatially integrated approach to enhance policy effectiveness.]]>
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