IMPLEMENTASI DATA MINING UNTUK MEMPREDIKSI KELULUSAN SISWA DENGAN METODE NAÏVE BAYES

  • Karolina Sinaga Universitas Putera Batam
  • Koko Handoko Universitas Putera Batam

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.

Published
2021-01-25
How to Cite
SINAGA, Karolina; HANDOKO, Koko. IMPLEMENTASI DATA MINING UNTUK MEMPREDIKSI KELULUSAN SISWA DENGAN METODE NAÏVE BAYES. Computer and Science Industrial Engineering (COMASIE), [S.l.], v. 4, n. 6, p. 97-107, jan. 2021. ISSN 2715-6265. Available at: <http://ejournal.upbatam.ac.id/index.php/comasiejournal/article/view/3585>. Date accessed: 02 mar. 2021.
Section
Articles