<![CDATA[The Integrated Information System (SITU) is an application used to support various academic services at Universitas Labuhanbatu. The quality of services provided by this application needs to be evaluated to determine the level of student satisfaction as its users. This study aims to analyze student satisfaction with the use of the Integrated Information System (SITU) using the Naïve Bayes and Decision Tree methods. The research applies the Knowledge Discovery in Databases (KDD) process, which consists of Selection, Preprocessing, Transformation, Data Mining, Evaluation, and Interpretation. The research data were collected through questionnaires distributed to 50 students of the Faculty of Science and Technology at Universitas Labuhanbatu. The research variables include System Ease of Use, System Access Speed, Information Accuracy, User Interface, and System Reliability, while the target variable is the student satisfaction level, classified into Satisfied and Dissatisfied categories. The classification process was carried out using Orange Data Mining software and evaluated using a Confusion Matrix. The interpretation results based on 27 testing data showed that the Decision Tree algorithm classified 19 instances as Satisfied and 8 instances as Dissatisfied, while the Naïve Bayes algorithm classified 18 instances as Satisfied and 9 instances as Dissatisfied. Furthermore, the Confusion Matrix evaluation indicated that the Naïve Bayes method achieved a 96.8% prediction accuracy for the Satisfied category, outperforming the Decision Tree method, which achieved 81.6%. Based on these results, the Naïve Bayes method demonstrated superior classification performance in analyzing student satisfaction with the Integrated Information System (SITU). The findings of this study are expected to serve as a reference for Universitas Labuhanbatu in evaluating and improving the quality of services provided through the Integrated Information System (SITU).]]>
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