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All Journal Router : Jurnal Teknik Informatika dan Terapan Router : Jurnal Teknik Informatika dan Terapan
Tiara Siti Nadira
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Computer Science & IT

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Implementasi Data Mining untuk Mengetahui Minat Baca Peserta Didik Menggunakan Naives Bayes pada Perpustakaan SMP Negeri 2 Palembang Tiara Siti Nadira; Tata Sutabri
Router : Jurnal Teknik Informatika dan Terapan Vol. 2 No. 4 (2024): Desember: Router: Jurnal Teknik Informatika dan Terapan
Publisher : Asosiasi Profesi Telekomunikasi dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/router.v2i4.302

Abstract

Students reading interest is a crucial factor in enhancing the quality of education. However, the lack of structured data makes it challenging to identify specific patterns of reading interest. This study aims to implement a data mining method using the Naive Bayes algorithm to analyze students' reading interest at SMP Negeri 2 Palembang's library. The data used includes book borrowing history, types of books, and library visit frequency over one semester. The analysis results indicate that the Naive Bayes method achieves an accuracy rate of 80% in classifying reading interest based on predetermined categories. These findings are expected to assist the school in designing more effective literacy programs.
Implementasi Data Mining untuk Mengetahui Minat Baca Peserta Didik Menggunakan Naives Bayes pada Perpustakaan SMP Negeri 2 Palembang Tiara Siti Nadira; Tata Sutabri
Router : Jurnal Teknik Informatika dan Terapan Vol. 2 No. 4 (2024): Desember : Router: Jurnal Teknik Informatika dan Terapan
Publisher : Asosiasi Profesi Telekomunikasi dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/router.v2i4.302

Abstract

Students reading interest is a crucial factor in enhancing the quality of education. However, the lack of structured data makes it challenging to identify specific patterns of reading interest. This study aims to implement a data mining method using the Naive Bayes algorithm to analyze students' reading interest at SMP Negeri 2 Palembang's library. The data used includes book borrowing history, types of books, and library visit frequency over one semester. The analysis results indicate that the Naive Bayes method achieves an accuracy rate of 80% in classifying reading interest based on predetermined categories. These findings are expected to assist the school in designing more effective literacy programs.
Co-Authors Alfin Cahyo Wibisono Tata Sutabri