<![CDATA[Higher education institutions play an important role in creating quality human resources, and one of the main factors that influence the quality of higher education is the academic services provided to students, as seen at STMIK Widuri. The Academic and Student Affairs Administration Bureau of STMIK Widuri needs to provide quick and accurate responses to ensure the quality of services is maintained. This study aims to predict the services of the Academic and Student Affairs Administration Bureau using the Naive Bayes Classifier algorithm, which is a probability-based classification method for predicting a class. The datasets used in this study are perceptions and expectations derived from questionnaires distributed online to STMIK Widuri students, which were processed using RapidMiner through the stages of Knowledge Discovery in Database (KDD). The evaluation results show an accuracy of 95%, precision of 100%, and recall of 93.75% for the perception dataset, and an accuracy of 90%, precision of 87.50%, and recall of 87.50% for the expectation dataset. This algorithm has proven to be effective in predicting the satisfaction of services provided by the Academic and Student Affairs Administration Bureau at STMIK Widuri.]]>
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