Feature Selection Klasifikasi Kategori Cerita Pendek Menggunakan Naïve Bayes dan Algoritme Genetika

Classification of short stories category based on age of the reader is still difficult. Therefore, a decision support system to classify the short stories category is needed. Naïve Bayes is one of methods suitable for short stories classification. However, Naïve Bayes has flaws in accuracy level, an...

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Main Authors: Oman Somantri, Mohammad Khambali
Format: Article
Language:English
Published: Universitas Gadjah Mada 2017-08-01
Series:Jurnal Nasional Teknik Elektro dan Teknologi Informasi
Subjects:
Online Access:http://ejnteti.jteti.ugm.ac.id/index.php/JNTETI/article/view/332
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author Oman Somantri
Mohammad Khambali
author_facet Oman Somantri
Mohammad Khambali
author_sort Oman Somantri
collection DOAJ
description Classification of short stories category based on age of the reader is still difficult. Therefore, a decision support system to classify the short stories category is needed. Naïve Bayes is one of methods suitable for short stories classification. However, Naïve Bayes has flaws in accuracy level, and needs to be optimized. In this paper, Genetic algorithm is proposed to increase the level of accuracy. In this case, genetic algorithm is used for feature selection. The results show an increase in the level of accuracy produced. The accuracy increases from 78,59% to 84,29%. In conclusion, the application of genetic algorithm on Naïve Bayes in classifying the online short stories category can improve the accuracy.
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spelling doaj.art-d6dd5b29c12d4f468bb83ff2218327ea2022-12-22T01:00:43ZengUniversitas Gadjah MadaJurnal Nasional Teknik Elektro dan Teknologi Informasi2301-41562460-57192017-08-016330130610.22146/jnteti.v6i3.332Feature Selection Klasifikasi Kategori Cerita Pendek Menggunakan Naïve Bayes dan Algoritme GenetikaOman Somantri0Mohammad Khambali 1Politeknik Harapan Bersama TegalPoliteknik Negeri SemarangClassification of short stories category based on age of the reader is still difficult. Therefore, a decision support system to classify the short stories category is needed. Naïve Bayes is one of methods suitable for short stories classification. However, Naïve Bayes has flaws in accuracy level, and needs to be optimized. In this paper, Genetic algorithm is proposed to increase the level of accuracy. In this case, genetic algorithm is used for feature selection. The results show an increase in the level of accuracy produced. The accuracy increases from 78,59% to 84,29%. In conclusion, the application of genetic algorithm on Naïve Bayes in classifying the online short stories category can improve the accuracy.http://ejnteti.jteti.ugm.ac.id/index.php/JNTETI/article/view/332klasifikasikategori cerpennaive bayesalgoritme genetika
spellingShingle Oman Somantri
Mohammad Khambali
Feature Selection Klasifikasi Kategori Cerita Pendek Menggunakan Naïve Bayes dan Algoritme Genetika
Jurnal Nasional Teknik Elektro dan Teknologi Informasi
klasifikasi
kategori cerpen
naive bayes
algoritme genetika
title Feature Selection Klasifikasi Kategori Cerita Pendek Menggunakan Naïve Bayes dan Algoritme Genetika
title_full Feature Selection Klasifikasi Kategori Cerita Pendek Menggunakan Naïve Bayes dan Algoritme Genetika
title_fullStr Feature Selection Klasifikasi Kategori Cerita Pendek Menggunakan Naïve Bayes dan Algoritme Genetika
title_full_unstemmed Feature Selection Klasifikasi Kategori Cerita Pendek Menggunakan Naïve Bayes dan Algoritme Genetika
title_short Feature Selection Klasifikasi Kategori Cerita Pendek Menggunakan Naïve Bayes dan Algoritme Genetika
title_sort feature selection klasifikasi kategori cerita pendek menggunakan naive bayes dan algoritme genetika
topic klasifikasi
kategori cerpen
naive bayes
algoritme genetika
url http://ejnteti.jteti.ugm.ac.id/index.php/JNTETI/article/view/332
work_keys_str_mv AT omansomantri featureselectionklasifikasikategoriceritapendekmenggunakannaivebayesdanalgoritmegenetika
AT mohammadkhambali featureselectionklasifikasikategoriceritapendekmenggunakannaivebayesdanalgoritmegenetika