<![CDATA[Extreme poverty in archipelagic regions is strongly shaped by geographical constraints such as inter-island isolation, weak connectivity, and high logistics and basic service costs, with the Riau Islands Province showing pronounced and uneven poverty across sub-districts. This study aims to analyze the relationship between geographical constraints and extreme poverty, as well as to identify spatial clustering patterns that can inform more targeted policy interventions. The study employs a quantitative approach using microdata on extremely poor households. The analysis applies Spearman’s rank correlation to examine the relationship between variables, along with Global Moran’s I and Local Indicators of Spatial Association to detect spatial autocorrelation and clustering patterns. The findings indicate a significant positive relationship between geographical constraints and extreme poverty, showing that stronger spatial barriers are associated with deeper and more severe poverty conditions. Spatial analysis further reveals the presence of distinct high-poverty clusters across several sub-districts in multiple regencies and cities. These results highlight the importance of place-based policy approaches that are sensitive to local spatial conditions. Such policies are essential for addressing uneven development and improving the effectiveness of poverty reduction strategies at the sub-district level in archipelagic regions.]]>
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