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Nisriina Nuur Hasanah
Universitas Mercu Buana Yogyakarta
Computer Science & IT Electrical & Electronics Engineering

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Implementasi Data Mining Untuk Pengelompokan Buku Menggunakan Algoritma K-Means Clustering (Studi Kasus : Perpustakaan Politeknik LPP Yogyakarta) Nisriina Nuur Hasanah; Agus Sidiq Purnomo
Jurnal Teknologi Dan Sistem Informasi Bisnis Vol 4 No 2 (2022): Juli 2022
Publisher : Prodi Sistem Informasi Universitas Dharma Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jteksis.v4i2.499

Abstract

LPP Yogyakarta Polytechnic Library is a facility provided as a learning resource. The number of collections available in the library makes it easier for students to access various knowledge. On the other hand, the available books come from donations, so there is still a lack of control over the availability of certain books. For example, books that are given by contributors are related to engineering sciences, while those that are sought after are books on plantation science. Based on these problems, in order to optimize the availability of books, it is necessary to analyze so that the ratio of availability and the number of enthusiasts is appropriate. One alternative is to implement data mining using the K-Means Clustering method to help library managers analyze by grouping books from the number of borrowed and the number of available copies so that they can be used to support the decision whether to reproduce books with related titles or not. The data used in this study is the history of borrowing books from the Yogyakarta LPP Polytechnic Library for approximately 2 years. The final result of the research in the form of book data is the most in demand, quite in demand, and the least in demand.
Co-Authors Agus Sidiq Purnomo