<![CDATA[The promotion process of Civil Servants (PNS) is a critical component of human resource management aimed at improving performance and professionalism. However, in practice, the process often faces challenges such as subjective assessments and inefficiencies in data processing. This study aims to develop a classification model for determining the eligibility of regular promotions for civil servants using the Decision Tree C4.5 algorithm based on historical personnel data. The dataset consists of 6,193 records obtained from the Regional Personnel and Human Resource Development Agency of Pangkajene and Kepulauan Regency. The attributes used include years of service, performance scores, and employment type. The research stages involve data preprocessing, feature selection, model construction, and evaluation using confusion matrix, accuracy, precision, recall, and F1-score. The results indicate that the proposed model achieves an accuracy of 95.4%, with precision of 87.6%, recall of 83.7%, and F1-score of 85.6%. Additionally, the model generates interpretable decision rules that support decision-making processes. Therefore, the application of data mining using the C4.5 algorithm is proven effective in enhancing objectivity, transparency, and efficiency in civil servant promotion decision-making]]>
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