Survival Analysis with Cox Proportional Hazard Regression Modeling (Case Study: Student Study Period Data on Engineering Faculty of Bangka Belitung University)

Authors

  • Ineu Sulistiana Universitas Bangka Belitung, Jalan Kampus Terpadu Universitas Bangka Belitung
  • Elyas Kustiawan Universitas Bangka Belitung, Jalan Kampus Terpadu Universitas Bangka Belitung
  • Ririn Amelia Universitas Bangka Belitung, Jalan Kampus Terpadu Universitas Bangka Belitung

DOI:

https://doi.org/10.29303/emj.v6i2.170

Keywords:

Kaplan Meier Estimation, Log Rank Test, Cox Regression, Maximum Likelihood Estimation, Hazard Ratio, Study Period

Abstract

Student study time is the time needed by students to complete their education, which starts from the time they enter college until they are declared graduated or have completed their study period. In the study period data, survival time observations were only carried out partially or not until the failure event. In other words, termination occurs until the observation deadline. This termination occurred due to several factors that allegedly influenced the student's study period. This study intends to determine what variables influence the study period of students of the Faculty of Engineering, University of Bangka Belitung through survival analysis. Using study period data for students of the Faculty of Engineering, University of Bangka Belitung, class of 2015/2016, this study used the Kaplan Meier Estimation to see the survival function of each factor causing the length of the study period graphically and the Log Rank Test statistically. Meanwhile, to look at the factors that determine the length of a student's study period, researchers used the Cox Regression and Maximum Likelihood Estimation (MLE) models to find the best model. The results of the data analysis show that there are differences in the survival function in each category for all variables graphically, while the statistical comparison of the results of the estimation of the survival function curve based on gender and organizational status is not significantly different. The results of the analysis also show that the proportional hazard assumption is fulfilled through the cumulative hazard log so that categorical variables can be used in the Cox Regression model. Based on the results of the likelihood estimation, the variables that have a significant effect on the study period of Engineering Faculty students are majors and GPA variables. Furthermore, from the interpretation of the model parameters, it is obtained that the Hazard Ratio (HR) value for the study period of Mechanical, Mining and Electrical Engineering students is faster than that of Civil Engineering students, while students with GPA ≥ 3.00 have a shorter study period than students with GPA < 3.00.

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Published

2023-12-31

How to Cite

Sulistiana, I., Kustiawan, E., & Amelia, R. (2023). Survival Analysis with Cox Proportional Hazard Regression Modeling (Case Study: Student Study Period Data on Engineering Faculty of Bangka Belitung University). EIGEN MATHEMATICS JOURNAL, 6(2), 75–83. https://doi.org/10.29303/emj.v6i2.170

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