<![CDATA[Economic uncertainty affects regions unevenly, while the Village Potential Census (Podes), as the most granular source of village-level data, is static and therefore has limited capacity to detect regional vulnerabilities at an early stage. This study integrates Podes data with remote sensing data to construct a Village Adaptive Capacity Index for 187 villages in Bekasi Regency using the Entropy-TOPSIS method. The robustness of the index is assessed, while its spatial patterns are further analyzed using Moran’s I, Local Indicators of Spatial Association, and K-means typology based on Principal Component Analysis (PCA). The data used in this study are derived from remote sensing imagery and the Village Potential Census conducted by Statistics Indonesia (BPS). The resulting Village Adaptive Capacity Index ranges from 0.134 to 0.764, with strong spatial autocorrelation. The regional typology reveals a Transition cluster, demonstrating that data integration can uncover hidden vulnerabilities that are not captured by Podes alone.]]>
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