Menentukan Kelompok Prioritas Penerima Bantuan Program Keluarga Harapan (PKH) Dengan Penerapan Data Mining Menggunakan Metode Clustering K-Means Di Desa Dagang Kelambir - Rahmat Syahroni; Didi Febrian (Pusat Riset dan Inovasi Nasional, 2026)
The Keluarga Harapan Program (PKH) is a government conditional social assistance program aimed at improving the welfare of low-income families. However, its implementation often faces issues in accurately targeting beneficiaries. Therefore, an objective method is needed to classify people based on their level of need. This study applies the K-Means clustering method to group PKH beneficiary families in Dagang Kelambir Village into clusters with similar characteristics. The variables used include age, number of dependents, occupation, income, and housing ownership status, with a total of 201 residents analyzed. Data processing was conducted using the R programming language, including normalization and the Elbow method to determine the optimal number of clusters. The results show three clusters: 124 families in the non-priority group, 39 in the secondary priority group, and 38 in the primary priority group. This method is effective in identifying priority groups objectively and supports more accurate and efficient distribution of PKH assistance.