Divorce Factor Classification Uses The C4.5 Algorithm Based On Particle Swarm Optimization

Abstract

Cases of household divorce increased in the West Java area during the Covid-19 pandemic. The pandemic has increased personal relationships and interactions between family members, and some families are using this opportunity to strengthen their relationships. However, increased family interaction can also result in increased conflict, leading to divorce. The author classifies divorce factors that have increased during the pandemic using the C4.5 Algorithm based on Particle Swarm Optimization (PSO). The main factors for divorce are economic factors that have hit during the pandemic coupled with unstable mental conditions resulting in poor communication and continuous fighting. So that the husband/wife leaves one of the parties, infidelity, and adultery, then domestic violence and ending in divorce. The dataset was taken from the West Java BPS website, and the author split the data, namely 80% training data and 20% testing data, to avoid overfitting. Research results on the classification of divorce factors during the pandemic using the C4.5 algorithm based on particle swarm optimization are an accuracy value of 87.50% and an AUC (Area Under Curve) value of 0.807, which is included in the good classification category.