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

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.