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All Journal JOMLAI: Journal of Machine Learning and Artificial Intelligence
Daud Siburian
STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
Computer Science & IT Engineering

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Implementation of K-Means Algorithm for Clustering Books Borrowing in School Libraries Daud Siburian; Sundari Retno Andani; Ika Purnama Sari
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 2 (2022): June
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (594.364 KB) | DOI: 10.55123/jomlai.v1i2.725

Abstract

The school library is an important resource in an effort to support the process of improving the quality of education in schools. Through the library a lot of information can be extracted and used for educational purposes. The library is expected to play its function as a vehicle for education, research, preservation, information, and recreation to improve the nation's intelligence. This study aims to cluster the borrowing of library books at SMA Assisi Pematangsiantar. The research data was obtained from the school library. The algorithm used for the clustering process is K-Means Clustering which is one of the data mining algorithms. The data was processed using Microsoft Excel and Rapid Miner 5.3 to determine the value of the centroid in 2 clusters, namely the highest and lowest clusters. Based on manual calculations with Microsoft Excel and testing with Rapid Miner, this study resulted in the same value, namely the highest cluster produced 6 types of books including Mathematics,. Geography, Chemistry, Civics, Physical Education and Computers. As for the lowest cluster, there are 6 types of books, namely Indonesian, English, Biology, Physics, Religion and Cultural Arts. So it can be concluded that the K-Means method in this study can cluster school library book borrowing well, referring to manual calculations and testing which have the same results
Co-Authors Ika Purnama Sari Sundari Retno Andani