DETERMINING STUDENT GRADUATION BASED ON SCHOOL LOCATION USING GEOGRAPHICALLY WEIGHTED LOGISTIC REGRESSION

  • Hendra Perdana Department Mathematics, Faculty of Mathematics and Science, Tanjungpura University, Indonesia
  • Neva Satyahadewi Department Mathematics, Faculty of Mathematics and Science, Tanjungpura University, Indonesia
  • Fritzgerald Muhammad Arsyi Department Mathematics, Faculty of Mathematics and Science, Tanjungpura University, Indonesia
DOI: https://doi.org/10.30598/barekengvol17iss4pp2273-2280
Keywords: Classification Accuracy, GWLR, Kernel Function, Logistic Regression, Spatial Data, Student Graduation

Abstract

Faculty of Mathematics and Natural Sciences (FMIPA) is one of the Faculties in Tanjungpura University with 9 Undergraduate Programs (S1). Based on the graduation data of the 2014 batch of FMIPA students, the number of students who did not complete their studies was 131 students or 29% of the total 445 students and 187 schools in Indonesia. If the study period of students can be predicted early, the study program can provide advice or recommendations so that students can complete their studies in/exactly 8 semesters. This study aims to determine the model for analyzing the factors that influence the graduation of FMIPA students using GWLR. Geographically Weighted Logistic Regression (GWLR) is a developing logistic regression model applied to spatial data. This model is used to predict data with binary dependent variables that consider the location characteristics of each observation. The units of observation in this study are the school location of 455 students spread across Indonesia. The variables used in this study were sourced from the Academic and Student Affairs Bureau UNTAN and divided into dependent variables (Y) and independent variables (X), i.e. Gender, college selection, Accreditation, School Type, School Location, and Name of Study Program. The dependent variable analyzed is the graduated status of FMIPA UNTAN students, i.e. completed and not completed their studies. The results showed that gender and the name of the study program are factors that affect the graduation of FMIPA UNTAN 2014 students with a classification accuracy of 72.6%.

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Published
2023-12-19
How to Cite
[1]
H. Perdana, N. Satyahadewi, and F. Arsyi, “DETERMINING STUDENT GRADUATION BASED ON SCHOOL LOCATION USING GEOGRAPHICALLY WEIGHTED LOGISTIC REGRESSION”, BAREKENG: J. Math. & App., vol. 17, no. 4, pp. 2273-2280, Dec. 2023.
Issue
Vol 17 No 4 (2023): BAREKENG: Journal of Mathematics and Its Applications
Section
Articles

Copyright (c) 2023 Hendra Perdana, Neva Satyahadewi, Fritzgerald Muhammad Arsyi

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