C4.5 Implementation to Predict the Rate of Resignation of Students in the University

Darsono Nababan, Parasian D. P. Silitonga, Magdalena Simanjuntak, Rusmin Saragih, Yoseph P. K. Kelen

2019

Abstract

Classification is a process in data mining that is used to find models or functions that explain or differentiate concepts or data classes. Classification of data is used to estimate a class of an object whose label is unknown. One of the classification models is in the form of a decision tree and decision rules. The main function of decision tree implementation is a decision tree's ability to break down the complex decision process into a simpler one. This study uses the C4.5 method which is used to form a decision tree carried out on the data of students at the University. Based on the decision tree that is produced, the causes that affect the resignation of college students can be found. The attributes that are used in the decision tree in this research are student Achievement Index Rating, parents' income and student attendance rate at lectures. Based on the results of the research conducted, it was concluded that the parents' small income factors and small Achievement Index Rating became the dominant factors that caused students to resign.

Paper Citation

in Harvard Style

Nababan D., Silitonga P., Simanjuntak M., Saragih R. and Kelen Y. (2019). C4.5 Implementation to Predict the Rate of Resignation of Students in the University.In Proceedings of the International Conferences on Information System and Technology - Volume 1: CONRIST, ISBN 978-989-758-453-4, pages 5-11. DOI: 10.5220/0009319600050011

in Bibtex Style

@conference{conrist19,
author={Darsono Nababan and Parasian D. P. Silitonga and Magdalena Simanjuntak and Rusmin Saragih and Yoseph P. K. Kelen},
title={C4.5 Implementation to Predict the Rate of Resignation of Students in the University},
booktitle={Proceedings of the International Conferences on Information System and Technology - Volume 1: CONRIST,},
year={2019},
pages={5-11},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009319600050011},
isbn={978-989-758-453-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the International Conferences on Information System and Technology - Volume 1: CONRIST,
TI - C4.5 Implementation to Predict the Rate of Resignation of Students in the University
SN - 978-989-758-453-4
AU - Nababan D.
AU - Silitonga P.
AU - Simanjuntak M.
AU - Saragih R.
AU - Kelen Y.
PY - 2019
SP - 5
EP - 11
DO - 10.5220/0009319600050011