Computer & Science Industrial Engineering Journal
Vol 4 No 6 (2021): Comasie

IMPLEMENTASI DATA MINING UNTUK MEMPREDIKSI KELULUSAN SISWA DENGAN METODE NAÏVE BAYES

Sinaga, Karolina (Unknown)
Handoko, Koko (Unknown)



Article Info

Publish Date
25 Jan 2021

Abstract

The problem of student grades is very important as a benchmark to see the level of student graduation. Effective value management with supporting applications that are very helpful in calculating accurate calculations. That way the use of naïve Bayes technology methods is able to answer problems in the information field of any integrated data. The purpose of this study was to determine the pass rate of students in the implementation of data mining for students who passed and did not pass, based on the final school examination scores (UAS), national test scores (UN), final scores (NA) for the last 3 years, 2017 to 2019. The data study method used in this research is by observation and interviews with resource persons from SMK Putra Jaya School Batam. The auxiliary application in the study used was WEKA to calculate student graduation results. This study used 70 student data as a test of value to be processed and produced a total of 210 data with 167 students who passed and 43 students who did not pass.

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Journal Info

Abbrev

comasiejournal

Publisher

Subject

Computer Science & IT

Description

Journal Comasie is a journal that combines 3 science namely informatics engineering, information systems and industrial engineering. The theme and scope can be seen in the scope section. This journal was created as a means of publicizing the results of research conducted by lecturers and students. ...