Prediction of Scholarship Recipients Using Hybrid Data Mining Method with Combination of K-Means and C4.5 Algorithms

International Journal of artificial intelligence research

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Field Value
 
Title Prediction of Scholarship Recipients Using Hybrid Data Mining Method with Combination of K-Means and C4.5 Algorithms
 
Creator Mardison, Mardison
Defit, Sarjon
Alturky, Shaza
 
Subject Computer Science
Hybrid Data Mining K-Means Algorithm C4.5 Algorithm Scholarship Recipient
 
Description Obtaining a scholarship is the desire of every student or student who studies, especially those who come from poor families. The scholarship can lighten the burden on parents who pay for these students and can streamline the lecture process. However, students do not know exactly what they have to do to get the scholarship. Aside from that, students naturally want to know what causes and conditions have the greatest impact on achievement. The objective of this research is how to predict which number of students among them are predicted to get a scholarship at the opening of the scholarship acceptance using the K-Means and C4.5 methods. Apart from that, the aim of this research is to discover how the K-Means algorithm conducts data clustering (clustering) of student data to determine if they will succeed or not, as well as how the C4.5 algorithm makes predictions against students who have been clustered together. The Rapid Miner program version 9.7.002 was used to process the data in this report. The results of this study were that out of 100 students, 32 students were not scholarship recipients and 68 students were scholarship recipients. Another result of this research is that out of 100 students it is predicted that 9 (9%) will receive scholarships and 91 (91%) will not receive scholarships.
 
Publisher STMIK Dharma Wacana
 
Contributor
 
Date 2021-07-30
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Identifier http://ijair.id/index.php/ijair/article/view/224
10.29099/ijair.v5i2.224
 
Source International Journal of Artificial Intelligence Research; Vol 5, No 2 (2021): December
2579-7298
10.29099/ijair.v5i2
 
Language en
 
Rights Copyright (c) 2021 International Journal of Artificial Intelligence Research
https://creativecommons.org/licenses/by-sa/4.0
 

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