Hybrid Data Mining with the Combination of K-Means Algorithm and C4.5 to Predict Student Achievement

International Journal of artificial intelligence research

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Title Hybrid Data Mining with the Combination of K-Means Algorithm and C4.5 to Predict Student Achievement
Creator Ramadhanu, Agung
Defit, Sarjon
Kareem, Shahab Wahhab
Subject Computer Science;
Hybrid Data Mining, K-Means Algorithm, C4.5 Algorithm, Student Achievement
Description Getting academic achievement is the dream of every student who studies at higher education, especially undergraduate level. Undergraduate students aspire to the highest achievement (champion) at the last achievement of their studies. However, students cannot predict whether these students with the habits that have been done and the current conditions will make them excel or not. Apart from that, of course, students also want to know what factors and conditions influence the achievement the most. The objective to be achieved in this research is how to predict which number of students among them are predicted to excel (champion) at the end of the semester with a combination of the K-Means and C4.5 methods. Besides, the purpose of this study reveals how the K-Means algorithm performs data clustering of student data who will excel or not and how the C4.5 algorithm predicts students who have been grouped. Data processing in this study uses the Rapid Miner software version 9.7.002. The result of this research is that it is easier to group data in numerical form than data in polynomial form. Other results in this study were that out of 100 students, 27 students (27%) were predicted to excel (champions) and 73 (73%) did not achieve (not champions).
Publisher STMIK Dharma Wacana
Date 2021-07-30
Type info:eu-repo/semantics/article
Peer-reviewed Article
Identifier http://ijair.id/index.php/ijair/article/view/225
Source International Journal of Artificial Intelligence Research; Vol 5, No 2 (2021): December
Language en
Rights Copyright (c) 2021 International Journal of Artificial Intelligence Research

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