INDONESIAN LANGUAGE CLASSIFICATION OF CYBERBULLING WORDS ON TWITTER USING ADABOOST AND NEURAL NETWORK METHODS

Jurnal Riset Informatika

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Field Value
 
Title INDONESIAN LANGUAGE CLASSIFICATION OF CYBERBULLING WORDS ON TWITTER USING ADABOOST AND NEURAL NETWORK METHODS
 
Creator Nugroho, Kristiawan
 
Description Cyberbullying is a very interesting research topic because of the development of communication technology, especially social media, which causes negative consequences where people can bully each other, causing victims and even suicide. The phenomenon of Cyberbullying detection has been widely researched using various approaches. In this study, the AdaBoost and Neural Network methods were used, which are machine learning methods in classifying Cyberbullying words from various comments taken from Twitter. Testing the classification results with these two methods produces an accuracy rate of 99.5% with Adaboost and 99.8% using the Neural Network method. Meanwhile, when compared to other methods, the results obtained an accuracy of 99.8% with SVM and Decision Tree, 99.5% with Random Forest. Based on the research results of the Neural Network method, SVM and Decision Tree are tested methods in detecting the word cyberbullying proven by achieving the highest level of accuracy in this study
 
Publisher Kresnamedia Publisher
 
Date 2021-03-01
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Format application/pdf
 
Identifier http://ejournal.kresnamediapublisher.com/index.php/jri/article/view/191
10.34288/jri.v3i2.191
 
Source Jurnal Riset Informatika; Vol 3 No 2 (2021): Period of March 2021; 93-100
2656-1735
2656-1743
10.34288/jri.v3i2
 
Language eng
 
Relation http://ejournal.kresnamediapublisher.com/index.php/jri/article/view/191/76
 
Rights Copyright (c) 2021 Kristiawan Nugroho
http://creativecommons.org/licenses/by-nc/4.0
 

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