<![CDATA[This research aims to optimize the evaluation process of social assistants in the Family Hope Program (PKH) managed by the Social Service of Padang Lawas Regency. Currently, the performance evaluation of PKH social assistants is conducted conventionally, lacking structured data analysis. This study employs the K-Means Clustering method to analyze 2016 performance data of 28 PKH social assistants, identifying patterns and grouping them based on performance. The research framework includes problem identification, solution analysis, literature review, data analysis, K-Means implementation, and clustering validation. Initial random centroid assignment followed by Euclidean Distance calculations iteratively refines the clustering. Results reveal three performance clusters: high-performing (8 assistants), low-performing (2 assistants), and average-performing (18 assistants). These clusters assist in making objective contract renewal recommendations. The study demonstrates K-Means Clustering's efficacy in social performance evaluation, offering insights for strategic decision-making in social services.]]>
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