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

Authors

  • Tiara Siti Nadira Universitas Bina Darma
  • Tata Sutabri Universitas Bina Darma

DOI:

https://doi.org/10.62951/router.v2i4.302

Keywords:

Data mining, Reading Interest, Naive Bayes, Library, Education

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.

 

Downloads

Download data is not yet available.

References

Abdurrahman, M. (2003). Pendidikan Bagi Anak Berkesulitan Belajar.

Eko, P. (2014). Data Mining Konsep dan Aplikasi Menggunakan Matlab. Yogyakarta.

Han. (2013). Data Mining Concepts and Techniques 3rd Edition. Morgan Kaufmann, USA. Morgan Kaufmann.

Karthika, S., & Sairam, N. (2015). A Naïve Bayesian Classifier for Educational Qualification. ,. Indian Journal of Science and Technology, 8(16), 1–5. https://doi.org/http://doi.org/10.17485/ijst/2015/v8i16/62055

M Asgari, S Ketabi, & Z Amirian. (2019). Interest-Based Language Teaching: EnhancingStudents’ Interest and Achievement in L2 Reading Iranian J. Language Teaching Research7(1) 61–75

Priansyah, E., & Sutabri, T. (2024). Analisis Sentimen Berbasis Naïve Bayes Pada Media Sosial Twitter Terhadap Hasil Pemilu Indonesia 2024. IJM: Indonesian Journal of Multidisciplinary, 2(3), 128-138.

Rahmawati. (2020). Komunitas Baca Rumah Luwu Sebagai Inovasi Sosial Untuk Meningkatkan Minat BacaDi Kbupaten Luwu. Jurnal BENING, 1-5.

R D Utami, D C Wibowo, & Y Susanti. (2018). Analisis Minat Membaca Siswa Pada KelasTinggi di Sekolah Dasar Negeri 01 Belitang J. Pendidikan Dasar PerKhasa 4(1) 179–188

R. Masri Sareb Putra. (2008). Menumbuhkan Minat Baca: Panduan Praktis bagi Pendidik, Orang Tua, dan Penerbit. PT. Macanan Jaya Cemerlang.

Romario. (2013). Penerapan Data Mining Pada Rsup Dr.Moh Hoesin Sumatera Selatan Untuk Pengelompokan Hasil Diagnosa Pasien Pengguna Asuransi Kesehatan Miskin (askin).

Tata Sutabri. (2012). Analisis Sistem Informasi. Penerbit Andi.

Tata Sutabri. (2012). Konsep Sistem Informasi. Penerbit Andi.

Thomas. (2004). Data Mining : Definition and Decision Tree Examples. e-book.

Turban. (2005). Decision Support System and Intelligent Systems - 7th ed. Pearson Education, Inc. Pearson Education, Inc. Dwi Prabantini (penterjemah). Sistem Pendukung Keputusan dan Sistem Cerdas. Penerbit ANDI.

Widodo, Y. B., Anggraeini, S. A., & Sutabri, T. (2021). Perancangan Sistem Pakar Diagnosis Penyakit Diabetes Berbasis Web Menggunakan Algoritma Naive Bayes. J. Teknol. Inform. dan Komput, 7(1), 112-123.

Downloads

Published

2024-12-02

How to Cite

Tiara Siti Nadira, & Tata Sutabri. (2024). Implementasi Data Mining untuk Mengetahui Minat Baca Peserta Didik Menggunakan Naives Bayes pada Perpustakaan SMP Negeri 2 Palembang. Router : Jurnal Teknik Informatika Dan Terapan, 2(4), 177–186. https://doi.org/10.62951/router.v2i4.302

Similar Articles

1 2 3 4 5 > >> 

You may also start an advanced similarity search for this article.

Most read articles by the same author(s)

1 2 > >>