Penerapan Clustering K-Means Untuk Mendukung Pengelolaan Koleksi Pada Perpustakaan Fakultas Teknik Universitas Negeri Gorontalo

Abstract

One of the facility units that acts as a supporter of student learning in a university is the library. The library is a place where there are various collections of libraries that can enrich the knowledge of visitors. Thus, the management of additional collections is important in supporting this. Currently, the addition of book collections in the UNG Engineering Faculty Library is only based on references from statistical data on best-selling books, lecturer recommendations and the latest books without considering which collections are of interest to students. This can have a negative impact if there are additional collections in categories or types of books that are less desirable to read which can cause problems from the service side and financial losses of the library. Moving on from this problem, the K-Means clustering method will be applied to classify the reading interest of library visitors in this case are students. The supporting variables that will be used in the grouping will be divided according to the origin of the student majors by category of books, stock, number of books borrowed and number of books read. This grouping is expected to be a recommendation for library managers in managing the addition of book collections in the UNG Faculty of Engineering library.