SURVIVAL ANALYSIS ON DATA OF STUDENTS NOT GRADUATING ON TIME USING WEIBULL REGRESSION, COX PROPORTIONAL HAZARDS REGRESSION, AND RANDOM SURVIVAL FOREST METHODS

This article presents a comprehensive study of the factors that influence the length of study data of undergraduate students at FMIPA UNIB class 2018 and 2019. This study is essential because observations show that many students study for more than 8 semesters. The purpose of this study is to determine the factors that significantly influence the length of study of undergraduate students. These factors can be internal and external. Survival analysis is the right method to identify these factors because ordinary regression analysis is unable to estimate survival data. Therefore, methods such as Weibull regression, Cox Proportional Hazards regression, and Random Survival Forest are used. This study does not compare the methods used because these methods are independent of each other, but have the same goal, namely, to determine the factors that influence the length of study of students. The data used in this study are data on the length of study of students from the 2018 and 2019 cohorts sourced from the academic subsection of FMIPA UNIB, with variables of GPA, gender, region of origin, university entry route, parents' occupation, type of study program, and length of study. The results showed that GPA and the type of study program significantly influenced the length of study in Weibull regression analysis. In Cox proportional hazard regression, the GPA variable is an influential factor, while using the Random Survival Forest method, all factors significantly influenced the length of study, with their respective levels of importance.