Implementation Naive Bayes Algorithm for Student Classification Based on Graduation Status

Authors

  • Ayundyah Kesumawati Statistics Department, Faculty of Mathematics and Natural Sciences, Islamic University of Indonesia (UII), 55584 Sleman, Yogyakarta, Indonesia)
  • Din Waikabu Statistics Department, Faculty of Mathematics and Natural Sciences, Islamic University of Indonesia (UII), 55584 Sleman, Yogyakarta, Indonesia)

DOI:

https://doi.org/10.31763/ijabis.v1i2.3

Keywords:

Naive Bayes, Graduation Status, Classification

Abstract

Length of study in college is a time it takes a student to have completed the study in college. Bachelor degree in achieving normal that it takes time for four years, but still there are students who completed their studies beyond normal limits (over four years). This such as influence on the value of accreditation of the institution. In this paper, we used five variables: grade point average (GPA), Concentration in High School, Sex, participation in assistance and city of residence, which are classified by the Graduation Status students over four years and less than equal to four years. The method used for the classification of a student's study time is Naive Bayes algorithm. This study investigated classification student based on Graduation Status in Department Statistics of the Islamic University of Indonesia. From the result, Naïve Bayes algorithm classification is quite good with accuracy value for Naïve Bayes is 81.18%.

Downloads

Published

2018-01-05

How to Cite

Kesumawati, A., & Waikabu, D. (2018). Implementation Naive Bayes Algorithm for Student Classification Based on Graduation Status. International Journal of Applied Business and Information Systems, 1(2), 6–12. https://doi.org/10.31763/ijabis.v1i2.3

Issue

Section

Articles