The Cash Social Assistance (BST) program is one of the government's efforts to provide assistance to community groups in need. In Medan Polonia District, BST distribution still faces challenges in efficiently registering and categorizing the recipient population. Therefore, this study aims to classify the BST recipient population using the K-means clustering method based on last education, monthly expenses, number of dependents and employment. This research method involves collecting data on the BST recipient population from the sub-district office and using the Rapid Miner application to carry out clustering analysis. The results of data grouping were identified into three clusters with different priority levels. Cluster 1 consists of residents with the highest priority level, while Cluster 2 and Cluster 3 have a lower priority level. So the names included in Cluster 1 consisting of Ahmad Surya, Joko Santoso, Eko Setiawan, Dewi Lestari, Agus Wijaya, Jaya Pratama, Rudi Hermawan and Andi Wijaya are considered as BST recipients with the highest priority.
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