<![CDATA[The increasing rate of divorce in Marbau Selatan Village reflects a broader trend in Indonesia and highlights an urgent social issue that threatens family resilience. This study applied the K-Means Clustering algorithm to analyze and classify divorce cases based on demographic and social characteristics. Data were collected from 85 divorce records registered between 2021 and 2025, focusing on key variables such as age, gender, case type, and cause of divorce. The clustering process generated three distinct groups, namely: conflicts and repeated disputes, abandonment by one party, and economic hardship. The results demonstrated that persistent conflicts represented the most dominant factor, followed by abandonment and financial problems. These findings suggest that K-Means is effective for revealing hidden patterns in divorce data, providing valuable insights for local stakeholders. The study contributes to data-driven policy recommendations, such as premarital counseling, family economic empowerment, and community-based mediation, to reduce divorce rates and improve household harmony in rural areas.]]>
