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Heri Yuliantoro
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Penggunaan Algoritma Naïve Bayes pada Klasifikasi Judul Proyek Akhir Berdasarkan Kelompok Bidang Kompetensi (KBK) Dini Nurmalasari; Heri Yuliantoro; Saleha Indri Yanti
Media Informatika Vol 22 No 2 (2023)
Publisher : P3M STMIK LIKMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37595/mediainfo.v22i2.174

Abstract

The Final Project is one of the graduation requirements that must be met by Caltex Riau Polytechnic students. The title of the final project is submitted by students through the SIAK system. Currently, students who submit titles will choose their own type of KBK from the inputted title. So that a problem arises where the title of the final project does not match the KBK it should or the KBK is wrong. This is due to the ignorance of students in analyzing the title data of the final project that will be submitted. For this reason, a system is needed to classify Final Project titles based on CBC automatically. The system created is a system that can classify KBK automatically based on the description of the title of the Final Project by using text mining methods and nave Bayes algorithms. The system can also detect the percentage of similarity of the entered title with the existing title in the system database. The algorithm used to generate the percentage of title similarity is cosine similarity with text mining method.