Implementasi Data Mining untuk Mengetahui Minat Baca Peserta Didik Menggunakan Naives Bayes pada Perpustakaan SMP Negeri 2 Palembang

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.

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Publication Details

Journal
Router
Published
2024-12-02
DOI
https://doi.org/10.62951/router.v2i4.302
Primary Topic
Edcuational Technology Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Implementasi Data Mining untuk Mengetahui Minat Baca Peserta Didik Menggunakan Naives Bayes pada Perpustakaan SMP Negeri 2 Palembang

Tiara Siti Nadira, Tata Sutabri
Router
Edcuational Technology Systems
article

Implementasi Data Mining untuk Mengetahui Minat Baca Peserta Didik Menggunakan Naives Bayes pada Perpustakaan SMP Negeri 2 Palembang

Tiara Siti Nadira, Tata Sutabri
article en

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.

RouterVol. 2(4)
Universitas Bina Darma (ID)
Openalex Percentile: Top 73%
Edcuational Technology Systems
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