<![CDATA[Data management regarding capacity building for State Civil Apparatus (ASN) human resources at the Directorate General of Regional Development, Ministry of Home Affairs, currently faces challenges in data processing, information presentation, and decision-making due to the suboptimal use of information technology. This study aims to develop a web-based information system for managing apparatus capacity-building data by employing the Naïve Bayes algorithm as a classification method to support decision-making. The research adopts a quantitative approach utilizing data mining methods, encompassing data collection, preprocessing, splitting data into training and testing sets, building a classification model using the Naïve Bayes algorithm, and evaluating the model via a Confusion Matrix. The system was developed using the Python programming language and the Streamlit framework, and was implemented using apparatus capacity-building data from the 2024–2026 period. The results demonstrate that the system can integrate data management processes, classify capacity-building levels into Low, Medium, and High categories, and automatically generate analytical dashboards and reports. Model evaluation yielded an accuracy rate of 66.67%, indicating that the Naïve Bayes algorithm delivers satisfactory classification performance to support decision-making in managing apparatus capacity building. Consequently, the developed system can enhance the effectiveness, efficiency, and accuracy of data management while supporting the monitoring and evaluation of competency development programs for the apparatus at the Directorate General of Regional Development, Ministry of Home Affairs.]]>
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