Journals Proceedings

Abstract

Universities need to have extensive capabilities in order to analyze students’ achievement levels which will help in making appropriate academic decisions. Conversely, academic decisions will result in changes in academic performance which need to be assessed periodically and over spans of time. In this work, the college completion model based on k-means clustering algorithm was utilized in the development of the proposed academic decision support system (DSS). The system utilized data from the university database while the client front-end ensures adequate presentation so as to reveal significant details and dependencies. The system can be used to automate the decision making process of administrators aiming to decrease the high rate of academic failure among students. A real case study in Isabela State University is presented using a dataset collected from 2009-2013.