Educational Data Mining in Graduation Rate and Grade Predictions Utilizing Hybrid Decision Tree and Naïve Bayes Classifier

La Ode Mohamad Zulfiqar, Nurul Renaningtias, M. Yoka Fathoni

2019

Abstract

The use of Educational Data Mining (EDM) in educational context has the probability to frame the extant models of teaching and learning by affording new solutions to the interaction problem. An educational domain like student related prediction become so essential in the higher learning institutions since it able to be presenting the rate of the students’ graduations. Through prediction, data is analyzing and able to afford big picture of trends and patterns for the management of the higher educations. Through this paper research we are presenting the utilization of the hybrid decision tree combined with the na¨ıve Bayes classifier. The result showing the accuracy of prediction for graduation rate and graduation grade is 72.73% on the highest value partition.

Paper Citation

in Harvard Style

Zulfiqar L., Renaningtias N. and Fathoni M. (2019). Educational Data Mining in Graduation Rate and Grade Predictions Utilizing Hybrid Decision Tree and Naïve Bayes Classifier.In Proceedings of the International Conferences on Information System and Technology - Volume 1: CONRIST, ISBN 978-989-758-453-4, pages 151-157. DOI: 10.5220/0009907101510157

in Bibtex Style

@conference{conrist19,
author={La Ode Mohamad Zulfiqar and Nurul Renaningtias and M. Yoka Fathoni},
title={Educational Data Mining in Graduation Rate and Grade Predictions Utilizing Hybrid Decision Tree and Naïve Bayes Classifier},
booktitle={Proceedings of the International Conferences on Information System and Technology - Volume 1: CONRIST,},
year={2019},
pages={151-157},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009907101510157},
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 - Educational Data Mining in Graduation Rate and Grade Predictions Utilizing Hybrid Decision Tree and Naïve Bayes Classifier
SN - 978-989-758-453-4
AU - Zulfiqar L.
AU - Renaningtias N.
AU - Fathoni M.
PY - 2019
SP - 151
EP - 157
DO - 10.5220/0009907101510157