Analisa Prestasi Siswa Berdasarkan Kedisiplinan, Nilai Hasil Belajar, Sosial Ekonomi dan Aktivitas Organisasi Menggunakan Algoritma Naïve Bayes

Devi Yunita, Perani Rosyani, Resti Amalia

Abstract


Student achievement is needed to measure the level of knowledge, intelligence, and skills of a person. Data mining is a combination of various fields of science, namely statistics, artificial intelligence, and databases. The purpose of education for students is to be able to change attitudes, perceptions, instill good behavior and instill knowledge and character. The purpose of this study is to be able to find out student achievement during learning as a school evaluation material to improve teaching patterns for students to be more accomplished. Research using the Naïve Bayes Algorithm produces a fairly good value of accuracy of 89%. the results of this study are expected to help to monitor early student academic achievement, in order to improve student achievement and quality.

Keywords


Data Mining, Student Achievement, Naïve Bayes

References


Kusrini, Emha Taufiq Luthfi. 2009. Algoritma Data Mining, Penerbit Andi, Yogyakarta

Eka Sabna, Muhardi, (2016), “Penerapan Data Mining Untuk Memprediksi Prestasi Akademik Mahasiswa Berdasarkan Dosen, Motivasi, Kedisiplinan, Ekonomi, dan Hasil Belajar”, Pekanbaru:STMIK Hang Tuah Pekanbaru

Sofi Defiyanti, (2014), “perbandingan: prediksi prestasi belajar mahasiswa menggunakan teknik data mining”, Karawang: Fakultas Ilmu Komputer Universitas Singaperbangsa

Linda Setiawati, (2015), “Faktor-Faktor Yang Mempengaruhi Prestasi Belajar Praktik Kejuruan Siswa Smk Program Studi Keahlian Teknik Komputer Dan Informatika”, NTB: SMK Negeri 2 Sumbawa

I Kadek Juni Arta, Gede Indrawan dan Gede Rasben Dantes, (2016), “Data Mining Rekomendasi Calon Mahasiswa Berprestasi Di Stmik Denpasar Menggunakan Metode Technique For Others Reference By Similarity To Ideal Solution”, Bali: Universitas Pendidikan Ganesha

Ni Komang Sri Julyantari dan I Ketut Dedy Suryawan, (2014), “Data Mining Prestasi Akademik Dengan Naive Bayes Berdasarkan Attribut Importance (AI)”, Bali: STMIK STIKOM

Imam Syaifuddin dan Reddy Alexandro Harianto, (2016), “analisa perbandingan teknik-teknik data mining untuk prediksi prestasi akademik siswa”, Surabaya: Sekolah Tinggi Teknik Surabaya




DOI: http://dx.doi.org/10.32493/informatika.v3i4.2032

Refbacks

  • There are currently no refbacks.


Copyright (c) 2019 Devi Yunita

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Jurnal Informatika Universitas Pamulang (ISSN: 2541-1004 e-ISSN: 2622-4615)



This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License