TELKOMNIKA Telecommunication, Computing, Electronics and Control
Comparison of the feature selection algorithm in educational data mining

TELKOMNIKA Telecommunication, Computing, Electronics and Control
Comparison of the feature selection algorithm in educational data mining

Classification
Decision
Educational data mining
Feature selection algorithm
Student academic

Student academic accomplishment is the foremost focus of every educational
institution. In developing student achievement in educational institutions, the
researchers finally created a new research area, namely educational data
mining (EDM). How the feature selection (FS) algorithm works is by
removing unrelated data from educational datasets; therefore, this algorithm
can improve the classification performance managed in EDM techniques. This
research presents an analysis of the performance of the FS algorithm from the
student dataset. The results received from other FS algorithms and classifiers
will help other researchers to gain some best combination regarding FS
algorithms and the classification. Selecting features that are relevant for
student forecast models is a sensitive problem to stakeholders in education
because they must make decisions based on the results of the prediction
models. For the future, our paper seeks to play a decisive part while developing
quality concerning education, as well as guiding different researchers in
conducting educational interventions.

Agung Triayudi, Iskandar Fitri

http://journal.uad.ac.id/index.php/TELKOMNIKA

May 15, 2021

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