Implementation Of Naive Bayes Classifier Algorithm On Social Media (Twitter) To The Teaching Of Indonesian Hate Speech

Fatahillah, Naufal Riza and Suryati, Pulut and Haryawan, Cosmas (2017) Implementation Of Naive Bayes Classifier Algorithm On Social Media (Twitter) To The Teaching Of Indonesian Hate Speech. International Conference on Sustainable Information Engineering and Technology (SIET). pp. 128-131.

[img] Text (Implementation Of Naive Bayes Classifier Algorithm On Social Media (Twitter) To The Teaching Of Indonesian Hate Speech)
SIET-2017.pdf - Published Version
Download (809kB)

Abstract

Twitter is a social media that is widely used as a sharing medium on the internet. There are tweets containing sentences shared by the user, thus they can be read by the other users. A lot of information can be obtained from Twitter. Twitter users can connect with the other Twitter users in an international scale.Technology that is growing as today can be used for various things, especially regarding the information distributed in social media, specifically Twitter. One of the problems derived from social media is that Twitter tweets containing speechesin the form of both positive and negative utterances. From the problems above, a research is required to classify tweets that contain positive and negative speeches orutterances using naive bayes classifier method. The results of this study are implemented into a system that can classify tweets on Twitter. The system is built using js Node technology and Naive Bayes classifier as the calculation method of classification. Based on the tests performed, the best accuracy generated by the systems using the Naive Bayes Classifier is 93%. Keywords: classify, Naive Bayes Classifier, Twitter, speech

Item Type: Article
Additional Information: Penulis: Naufal Riza Fatahillah, Pulut Suryati, dan Cosmas Haryawan
Uncontrolled Keywords: classify, Naive Bayes Classifier, Twitter, speech
Subjects: A Karya Umum (General) > Ilmu Komputer (Computer Science) > Teknologi Informasi
Divisions: Jurnal (Journal)
Depositing User: Titis Pratiwi
Date Deposited: 03 Apr 2023 01:33
Last Modified: 03 Apr 2023 01:33
URI: http://eprints.utdi.ac.id/id/eprint/9947

Actions (login required)

View Item View Item
UTDI Repository is powered by EPrints 3 which is developed by the School of Electronics and Computer Science at the University of Southampton. More information and software credits.