Julia Jurnal
Vol 5 No 1 (2025): Julia Jurnal

PREDIKSI TINGKAT KELULUSAN PESERTA DIDIK SMK FATHUL ULUM GABUS DENGAN METODE NAIVE BAYES

Wahyudi (Unknown)
Eko Supriyadi (Unknown)
Andri Triyono (Unknown)



Article Info

Publish Date
13 Aug 2025

Abstract

The graduation of students refers to those who are able to complete and meet the graduation requirements set through a graduation meeting based on the decision letter signed by the school principal. Graduation rate data can be used to help make policies and strategies for the school to improve graduation rates in the following year. This study utilizes classification or prediction methods to analyze the graduation rates of students at SMK Fathul Ulum Gabus. The method used in this study is Naive Bayes, using variables such as practical exam scores, school exam scores, competency test scores, student attendance, and student behavior. The purpose of this study is to test the accuracy of the Naive Bayes method in predicting graduation rates based on data collected from 2019 to 2024. The research process includes data collection, data integration, and model training using Naive Bayes, which produces fairly accurate predictions with an accuracy of 94.64%. Based on this accuracy, it can be concluded that the Naive Bayes method can be used to predict graduation rates at SMK Fathul Ulum Gabus.

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Journal Info

Abbrev

1

Publisher

Subject

Computer Science & IT

Description

Julia is an open access journal. Readers may read, download, copy, distribute, print, search, or link to the full text of this article free of charge. All submitted papers will be peer reviewed before being accepted for publication. Authors who wish to submit manuscripts to Julia must follow the ...