Klasifikasi Text Judul Buku Perpustakaan Untuk Menentukan Kategori Buku Menggunakan K-Nearest Neighbor - Muhamad Kadafi (Systemic: Information System and Informatics Journal, 2020)
The need for information in the form of books or scientific articles at the Library of UIN Raden Fatah Palembang continues to increase. To make it easier to find book information, one of which is by classifying books based on the type of category. In classifying library book data, the Nearest Neighbor Classifier method in data mining can be combined with text data extraction techniques to classify library book title text data. The purpose of this study was to classify the text title of library books using the Nearest Neighbor Classifier to determine the type of book category. This research method uses the Nearest Neighbor Classifier data mining classification technique. The results of this study are that the highest accuracy value is found at K = 12, which is 72.50%, and the model formed can be used to classify books with labels 2x0, 150, 2x2, 400, 020, 2x1, 657, 500, 375, 302.2, 800. and cannot be used for classifying books with class labels 070, 370, 330, 300, 600, 340, 700.