Rancang Bangun Sistem Klasifikasi Kategori Buku dengan Algoritma Naïve Bayes Classifier (Studi Kasus : Perpustakaan Universitas Dinamika) - Casmina, Casmina; Nurcahyawati, Vivine; Lemantara, Julianto (Jurnal Sistem Informasi Universitas Dinamika, 2021)
Dinamika University library has an online catalog to search for books. to determine the category / class referring to the ddc23 book takes approximately 3 to 10 minutes. the problem that exists is that the library manager has difficulty determining the appropriate category because the determination of the category is not fast enough. the purpose of this research is to produce a book category classification system with the naïve bayes classifier algorithm (case study: undika library) to determine classification quickly and improve the suitability of book categories. naïve bayes classifier is a method used for classification in which the process is divided into two stages, namely the learning stage and the testing phase. classification uses class 000 of ddc23, where the data is divided into 311 training data and 78 testing data and the results of the accuracy test are 73% which shows the naïve bayes classifier algorithm can be used as an algorithm for classifying book categories because of its high accuracy. the level of testing accuracy is influenced by the large amount of training data and the category dictionary used. Classification of categories is done in a faster time with the system only takes 24 seconds 39 milliseconds.