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Mira Nanda Ambarita
Universitas Labuhanbatu, Indonesia
Aerospace Engineering Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics

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Analisis Prediksi Prestasi Siswa UPTD SD Negeri 30 Aek Batu dalam Machine Learning dengan Metode Naive Bayes Mira Nanda Ambarita; Marnis Nasution; Rahma Mutiah
Jurnal Syntax Admiration Vol. 5 No. 8 (2024): Jurnal Syntax Admiration
Publisher : Syntax Corporation Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46799/jsa.v5i8.1493

Abstract

This study aims to analyze and predict student achievement at UPTD SD Negeri 30 Aek Batu using a machine learning method with the Naive Bayes algorithm. By collecting data that includes academic grades, attendance, and other factors, the study cleans and processes the data to build a prediction model. The Naive Bayes algorithm is applied to identify patterns and relationships between these variables and student achievement. The results of this model are evaluated to determine its accuracy and ability to predict student performance, thereby providing valuable information for educational improvement strategies and interventions in schools.
Co-Authors Marnis Nasution Rahma Muti’ah