Intelligent System to Predict University Students Dropout

The objective of this research is to reduce the dropout rate students in Faculty Systems Engineering and Informatics Universidad Nacional Mayor de San Marcos – FISI-UNMSM, through implementation an intelligent system with a data mining approach autonomous learning algorithm (decision trees) that predicts which are at risk dropping out. It was developed Python free software Weka, for purpose student collected from 2014 2020. This solution increases availability level satisfaction faculty; process, accuracy percentage 90.34% precision 95.91% obtained, so model considered valid. In addition, it found variables most influenced making decision abandon their studies were historical weighted average, average last cycle number credits passed.