Optimasi Algoritma Genetika Dalam Memprediksi Minat Baca Siswa Pada Perpustakaan SMK Negeri 1 Gantar Dengan Metode Decision Tree - Lina Yulita; Aswan S Sunge; Nisa Nurhidayanti (DPPM Universitas Pelita Bangsa, 2022)
Students are one part of the world of education that cannot be separated from reading activities. Each school certainly seeks to provide reading facilities such as school libraries, as well as libraries owned by SMK Negeri 1 Gantar aim to be able to foster and increase students' interest in reading books in the school library. But at the moment the library of SMK Negeri 1 Gantar tends to be minimal in number of visitors, this could be due to the lack of student awareness of the importance of reading books or there are other factors that can influence such as service, type of book, comfort, collection of books and so on. Then conducted a study that aims to find out how much interest in reading students of SMK Negeri 1 Gantar library using genetic algorithm optimization with the decision tree method. The data used in this study are visitor data owned by the library of SMK Negeri 1 Gantar as many as 290 data, the process of testing the method using RapidMiner 9.2. Based on the results of testing on research in predicting students' reading interest in the library of SMK Negeri 1 Gantar, the results obtained from the C4.5 algorithm or decision tree are accuracy by 84.48% and after being optimized using genetic algorithms the accuracy increases by 12.07% so that the accuracy value obtained from optimization of 96.55%. Then it can be concluded that the genetic algorithm optimization technique in value succeeded in increasing the accuracy of the C4.5 algorithm or decision tree in predicting students' interest in reading at the SMK Negeri 1 Gantar library. Keyword: Reading interest, library, C4.5 algorithm, genetic algorithm.