Data Mining, Decision Tree, C4.5, Community Satisfaction Index - Doan Sefriyansyah; Sapri Sapri; Desi Mahdalena; Devi Sartika (LPPJPHKI Universitas Dehasen Bengkulu, 2026)
This study aims to apply a data mining method based on the C4.5 Decision Tree algorithm to classify the Public Satisfaction Index (PSI) regarding services at the Central Aceh District Attorney’s Office. Until now, the data from the CSI questionnaires collected has not been optimally utilized because it has only been processed using average calculations, thus failing to provide in-depth information regarding patterns of public satisfaction. The C4.5 Decision Tree method was used because it is capable of producing a classification model that is easy to understand and can identify the service attributes that most influence the level of public satisfaction. The data used in this study were derived from questionnaire results based on seven criteria: service procedures, service information, processing time, staff competence, technological facilities, complaint handling, and integrity. The results indicate that the C4.5 algorithm can be effectively applied to classify levels of public satisfaction and generate decision trees that serve as a basis for evaluation and decision-making.