<![CDATA[This study examines the effectiveness of the Non-Cash Food Assistance Program (BPNT) in alleviating poverty in Aceh Province, the poorest province on the island of Sumatra. The research utilizes data from the 2022 National Socioeconomic Survey (Susenas) to analyze household characteristics and determine factors influencing BPNT eligibility. Binary logistic regression and data balancing with SMOTE were applied to assess classification accuracy. Results indicate that households without adequate basic amenities, such as proper toilets and electricity, and those with limited access to resources, such as well water, firewood for cooking, and lack of household assets, are more likely to qualify for BPNT. The logistic regression model achieved an accuracy of 80.83%, with high recall for "Recipient" classification. This study findings highlight is that economic hardship, household size, and physical conditions are significant determinants of BPNT eligibility. This study suggests that targeted assistance for poverty alleviation can be optimized through refined eligibility criteria and data accuracy improvements.]]>
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