<![CDATA[The distribution of social assistance is one of the government's efforts to improve the welfare of the community,especially for low-income families. In the village of Purisemanding, the process of distributing Direct CashAssistance (BLT) often faces challenges in identifying the right recipients due to the manual data collectionmethods that are prone to errors and manipulation. This study aims to implement the K-Nearest Neighbor (KNN)method in the classification system for social assistance recipients to enhance the accuracy and efficiency ofBLT distribution. The study concludes that the use of the KNN method in the classification system for socialassistance recipients can improve objectivity in the process of determining recipients. This, in turn, affects theefficiency of the data collection and distribution process. This system is expected to be a practical solution forvillage governments in addressing the issues related to social assistance distribution that have been encounteredso far.Keywords: K-Nearest Neighbor, KNN, classification, social assistance, Purisemanding Village.]]>
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