Application of Clustering on Divorce Data in Indonesia Using BIRCH Algorithm
Keywords:
Clustering, BIRCH, Perceraian, PCAAbstract
Divorce is one of the social issues that has an impact on life, from adults to children. Divorce is influenced by many factors, ranging from economics, incompatibility, to the availability of technology. Therefore, appropriate efforts are needed to reduce the divorce rate. One approach that can be used is clustering using the BIRCH (Balanced Iterative Reducing and Clustering Using Hierarcics) algorithm based on divorce factors across all provinces in Indonesia. The study utilised 10 clusters, ranging from cluster 0 to 9. The research method employed was KDD. Data processing was conducted using Google Colab with the Python programming language. Based on the clustering results, different dominant factors were identified for each cluster. Cluster 2 has the most members, with 6 provinces, where the causes of divorce are abandonment by the spouse and gambling. This study produced a system for applying the BIRCH algorithm to divorce data, which can serve as a reference for the government to reduce divorce rates based on triggering factors in each region.
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