Analisis Prediksi Prestasi Siswa UPTD SD Negeri 30 Aek Batu dalam Machine Learning dengan Metode Naive Bayes

Mira Nanda Ambarita (Universitas Labuhanbatu, Indonesia)
Marnis Nasution (Universitas Labuhanbatu, Indonesia)
Rahma Mutiah (Universitas Labuhanbatu, Indonesia)

jurnal syntax admiration
Vol. 5 No. 8 (2024): Jurnal Syntax Admiration

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.