PENGELOMPOKKAN PEMINJAMAN BUKU BERDASARKAN TIPE PEMBACA DAN KATEGORI BUKU MENGGUNAKAN ALGORITMA K-MEANS PADA PERPUSTAKAAN SEKOLAH

Abstract

School libraries play a vital role in supporting the learning process. However, manual management of book borrowing data often complicates pattern analysis. This study aims to apply the K-Means Clustering algorithm to group borrowing data based on reader type, book category, and loan duration. The research was conducted at SMP Negeri 1 Kuala using historical borrowing data. The results show that K-Means effectively classifies borrowing patterns, helping librarians identify popular and less popular books. This approach supports data-driven decision-making in improving library collection management