Implementation of the C4.5 Algorithm in Determining Priority Locations for Family Planning (KB) Program Counseling

Abstract

Indonesia is one of the most populous countries in the world due to its high population growth rate. To suppress this rate, the government runs the Family Planning Program (Keluarga Berencana/KB). However, KB counseling has not been fully on target because the determination of counseling locations has not been based on adequate data analysis. This study aims to apply the C4.5 algorithm to classify birth data so that priority locations for KB counseling can be determined. The C4.5 algorithm is a data mining technique that builds a decision tree from training data. The data were obtained from the birth database of the Population and Civil Registry Office of Dumai City, comprising 934 records, divided into 70% training data and 30% testing data, and processed using the WEKA tool. The test results show that the C4.5 classification model achieved an accuracy of 99.5% with precision and recall values of 0.995. Based on the resulting decision tree, three urban villages (kelurahan) were identified as priority counseling locations, namely Jaya Mukti, Buluh Kasap, and Bukit Batrem. Therefore, the C4.5 algorithm is proven applicable for determining priority locations of Family Planning Program counseling.