Identification of Book Needs Level Using the K-Means Method at STMIK Pelita Nusantara Medan Library

Library Sekolah Tinggi Manajemen Ilmu Komputer Pelita Nusantara Medan is one of the facilities that provide book loan services to students. To improve services to the needs of books for Pelita Nusantara STMIK students. This test aims to determine the amount of books needed to borrow, and determine how many students borrow books based on books that are often borrowed simultaneously. The method used is the K-Means method, the K-Means algorithm is a non-hierarchical data clustering method with an effort to partition the available data into one or even more clusters. The data to be used is the amount of book data that is often borrowed, and the number of students who borrow books in 2015-2019. From the results obtained in the overall data process above that cluster 0 is a low-potential book borrower totaling 52 titles, Cluster 1 is a potential borrower of 30 books, and Cluster 2 is a high-potential book borrower totaling 1 book title, therefore knowledge is obtained that borrowing books at STMIK Pelita Nusantara books that are often borrowed will be reviewed for books. K-Means algorithm method has been able to be applied to identify the level of book requirements. Data is processed to obtain the number of books that are often borrowed will be multiplied. The data is processed using Rapid Miner software