Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
Vol 5, No 4 (2024): Edisi Oktober

Prediksi Prestasi Siswa SMAN 1 Muntok Berdasarkan Motivasi, Kedisiplinan, dan Sosial Ekonomi dengan Naïve Bayes

Endraswari, Putri Mentari (Unknown)
Tou, Nurhaeka (Unknown)



Article Info

Publish Date
30 Oct 2024

Abstract

This study aims to predict the achievement of class X students at SMA Negeri 1 Muntok by classifying socio-economic data (parents' income), student learning motivation, and student discipline using the Naive Bayes machine learning method. The approach taken in this study is quantitative, with a total of 104 students from 286 class X students who have gone through the data cleansing stage. Data collection was carried out through distribution and documentation. The Naïve Bayes method is used as a prediction analysis technique with the Python programming language. This study shows that the use of this method has an accuracy of 71%, with the prediction results of socio-economic variables, motivation, and discipline on student achievement showing that the discipline variable shows a stronger correlation with student achievement, compared to other variables.

Copyrights © 2024






Journal Info

Abbrev

kesatria

Publisher

Subject

Computer Science & IT Control & Systems Engineering

Description

KESATRIA: Jurnal Penerapan Sistem Informasi (Komputer & Manajemen) adalah sebuah jurnal peer-review secara online yang diterbitkan bertujuan sebagai sebuah forum penerbitan tingkat nasional di Indonesia bagi para peneliti, profesional, Mahasiswa dan praktisi dari industri dalam bidang Ilmu ...