<![CDATA[Abstract A student's graduation time is one indicator of the university's success. Student graduation time is the period required for students to complete their studies. Ideally, students can graduate on time under a specified study period. However, not all students can graduate on time. This study is aimed at classifying whether students graduate on time using the decision tree method. The data employed in this study are the Faculty of Law's graduates of 2015 - 2017, Universitas Ichsan Gorontalo. The attributes used in this classification consist of IPS1, PIS2, IPS3, IPS4, gender, and graduation information. In this study, model optimization performed is by selecting attributes, pruning trees, and measuring inside the tree. The results of this study show that the decision tree method can predict student graduation times with 92% accuracy by producing nine (9) decision rules. It indicates that the decision tree method can be a solution for predicting student graduation times, so it can be a solution to help study programs increase student success in completing their studies. Keywords: classification, graduation time, students, data mining, decision tree, accurate graduation]]>
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