Analisis Faktor Risiko Keterlambatan Kelulusan Mahasiswa Dengan Regresi Logistik Biner - Indah Simamora; Fransiska Atrik Halim; Carolin Dwija Novandini (Griya Journal of Mathematics Education and Application, 2026)
Delayed graduation is one of the academic issues that can affect the effectiveness of higher education management and the quality of graduates. This problem is also experienced by students of the Mathematics Education Study Program at Universitas Nusa Cendana, where many students have not completed their studies on time. This study aims to identify the factors influencing the risk of delayed graduation among students of the Mathematics Education Study Program at Universitas Nusa Cendana using a binary logistic regression model, considering both academic and non-academic factors. It also aims to determine the most dominant factor contributing to delayed graduation and to evaluate the model’s ability to classify and predict students’ graduation status. The dependent variable is graduation status, categorized as delayed graduation and on-time graduation. The independent variables include academic and non-academic factors. This study uses primary data collected through questionnaires distributed to students of the Mathematics Education Study Program at Universitas Nusa Cendana. The sample consisted of 96 students from the 2021/2022 cohort. The results indicate that gender, the number of repeated courses, and learning motivation significantly influence delayed graduation. The binary logistic regression model was able to predict students’ graduation status with an accuracy rate of 88.5%.