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Journal : Journal of Practical Computer Science (JPCS)

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
Journal of Practical Computer Science Vol. 2 No. 1 (2022): Mei 2022
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/jpcs.v2i1.949

Abstract

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.
Co-Authors Agus Jatnika Effendi Agus Riyadi Agus Riyadi Akhmad Khawari Amali, Amali Ana Fitrotun Nisa Andini Putri Riandani Angga Bahrul Fahmi Arum Tarina Asep Muhidin Aswan S Sunge Ayu Wahyuningtyas Budiarto, Eko Cici Arinih Dadang Heri Kusumah Daspar Daspar Dema Puji Lazuardini Deni Rusli Dewi, Rahma Dhonny Suwazan Dhonny Suwazan Dhonny Suwazan Dhora Jati, Erwika Dodit Ardiatma Dyah Wulandari Putri Edi Widodo Efendi L, Rudi Endah Yaodah Kodratillah Erina Rulianti Febrinasari, Tantry FITRI REZEKI Halomoan, Nico Harry Fadillah Pratama Helbi Nurul Huda Hendrian Nunggu Huda, Miftakul Ika Juhriati Ikhsan Romli Indah Yulian Kusuma Wardani Inna Nisawati Mardiani Ismi Trialfhianty, Tyas Isyulianto Isyulianto Jamaludin Tasdik Jati, Erwika Dhora Jayawarsa, A.A. Ketut Lina Yulita Mamad Nurahmad Martin Dharma Setiawan Maulana, Donny Meika Hikmatriana Miftakul Huda Mindriany Syafila Nadia Fitra Firnadi Nadya Ulfani Sara Nani Hartati Nasution Nasution Neny Mulyani Nida An Khofiyah Nisawati, Inna Novi Justika Harini Nur Ilman Ilyas Nur'aeni, Nur'aeni Nurpribadi, Giri Puspita Sari, Intan Putra, Maha Putri Anggun Sari Putri Riandani, Andini Ramadhani RDS, Yunita Retno Fitri Astuti REZEKI, FITRI Riandani, Andini Putri Rustianah, Rustianah Sandy Nugraha Sari, Putri Anggun Serta Manullang Setiawan , Martin Darma Simbar Fatih Buari Siti Rahayu Sofianti Sofianti Suherman Suherman Supriyanto Supriyanto Supriyanto Supriyanto Supriyati . Suri, Anita Tan, Emmelia Tata Tarnita TITIN SUNARYATI Tri Ngudi Wiyatno Widya, Adi Rusdi Winda Yulianti Wiyanto Wiyanto Yuli Winarto Yuni Hertati