<![CDATA[PT PLN (Persero), a State-Owned Enterprise (SOE), is mandated by Law No. 30/2007 on Energy and Law No. 30/2009 on Electricity to provide subsidy funds for the poor. The objective of this study is to analyze eligibility criteria for electricity subsidy recipients for customers using 450 VA and 900 VA power groups, to target the electricity subsidy program better. The data used is postpaid customer data from UP3 Bandung in September 2023. The variables used are the amount of electricity consumption, the number of bills, late fees, installment fees, and 50 other variables. The method used in this research is DBScan Clustering which is applied to each power group. Within each group, we analyzed two normalized versions of the dataset standard version and the minmax version. Furthermore, to assess the optimal clustering results, we integrated various metrics, including the Davies-Bouldin Index and Silhouette Score with visual assessment. After that, the best factor suggestions were sought through decision trees, by performing different decision tree classifiers for each power group, using normalized versions of cluster labels. The results showed that among the 50 features available in the raw dataset, it was successful in identifying key features, such as late fees, installment fees, electricity consumption, and bill charges to be important criteria]]>
Copyrights © 2024
