<![CDATA[This study examines divorce in East Java through a psychosocial analysis using machine learning and artificial intelligence. This investigation seeks to uncover the determinants that frequently occur in divorce cases. The study utilizes a blended methodology, integrating a review of literature, secondary data analysis from Indonesia’s Central Bureau of Statistics (BPS), and qualitative interviews. To forecast divorce, machine learning approaches such as Support Vector Machine (SVM), Random Forest, Neural Network, and Decision Tree were implemented outcomes based on factors such as economic issues, infidelity, domestic violence, and gambling. The results indicate that continuous disputes and quarrels are the primary causes of divorce, with gambling identified as a significant predictor. The Neural Network model achieved the highest AUC (0.896), while SVM showed potential class bias issues. The study highlights the complex interplay of psychosocial factors in divorce and underscores the importance of addressing these issues through targeted interventions]]>
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