Analysis Of UMN Student Graduation Timeliness Using Supervised Learning Method

Education is one of the most important things in human life, and world education. However, there are still many students who graduate not on time. The purpose this study to find out an overview what factors influence, then data analysis, visualization so that can time or for UMN student graduates 2018-2020. method approach used solve problem collection, independent variable, dependent CRISP-DM, with SQLYog tools, store data, rapid miner cleaning, calculate prediction accuracy using nave Bayes algorithm, regression logistics, included 10-fold validation method, visualizing Tableau.