Article Per Year (5 Year)
p-Index From 2019 - 2024
0.23
P-Index
This Author published in this journals
All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA
Michal Dennis
STMIK Amik Riau, Pekanbaru
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Penerapan Algoritma Naïve Bayes Untuk Pengelompokkan Predikat Peserta Uji Kemahiran Berbahasa Indonesia Michal Dennis; Rahmaddeni Rahmaddeni; Fransiskus Zoromi; M. Khairul Anam
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 2 (2022): April 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i2.3956

Abstract

Indonesian Language Proficiency Test is a proficiency test to measure a person's language proficiency in communicating using Indonesian, both Indonesian speakers and foreign speakers. The UKBI rating has 7 rating categories consisting of special, very excellent, excellent, intermediate, poor, marginal, and limited. The number of participants who take UKBI at the Riau Province Language Center has more than 1000 but no one has managed the data into new knowledge. One of the efforts that can be done with the data is classification. The Naïve Bayes Classification Algorithm is a classification algorithm that is very effective (getting the right results) and efficient (the reasoning process is carried out by utilizing existing inputs in a relatively fast way). In order to obtain good accuracy results, the Naive Bayes Algorithm is combined with the Adaboost feature selection with a 70:30 and 80:20 test scheme. The results of the research carried out resulted in the highest accuracy value, namely 89% which combined the Naive Bayes algorithm with the Adaboost feature selection with 70:30 data splitting
Co-Authors Anam, M Khairul Fransiskus Zoromi Rahmaddeni Rahmaddeni