Predictive Model of Student Academic Performance in Private Higher Education Institution (Case in Undergraduate Management Program)

Abstract

A private university must consider many things in accepting prospective students. Students enrolled are expected to stay until their studies are completed, have good academic performance, and be able to graduate on time. Private universities, from the beginning of the admission of new students, it is necessary to choose which prospective students are accepted to achieve the quality of education goals in the study program. This work aims to study the prediction class and class order of variable importance to students’ length of stay and academic performance labeled graduation. The method adopted falls into a technique called feature extraction. This study uses rank methods information gain and gain ratio to confront other methods χ2 and random forest. A dataset of 7676 observations, spanning the years from 2010-2021, students from a management program of a private university in Indonesia, is used. This study collects data from the faculty-specific department from the university’s academic admissions as inputs. The result of the study shows that all techniques vote IP/GPA (IP) as the most critical feature in predicting length of stay and graduation. Origin of High School, Selection Test Score, and Gender get split votes. This study is unique because it sheds light on the case particularity to Indonesia.