Hoax Identification of Indonesian Tweeters using Ensemble Classifier

Syaifuddiin, Gus Nanang, Arifin, Rizal, Desriyanti, Desriyanti, Buntoro, Ghulam Asrofi, Rosyidin, Zulkham Umar, Pratama, Ridwan Yudha and Selamat, Ali (2023) Hoax Identification of Indonesian Tweeters using Ensemble Classifier. Journal of Information Systems and Telecommunication, 11 (2). pp. 94-101. ISSN ISSN 2322-1437 / EISSN:2345-2773

	Text Artikel JIST.pdf Download (507kB)
	Text Plagiasi Artikel JIST.pdf Download (2MB)

Abstract

Fake information, better known as hoaxes, is often found on social media. Currently, social media is not only used to make friends or socialize with friends online, but some use it to spread hate speech and false information. Hoaxes are very dangerous in social life, especially in countries with large populations and ethnically diverse cultures, such as Indonesia. Although there have been many studies on detecting false information, the accuracy and efficiency still need to be improved. To help prevent the spread of these hoaxes, we built a model to identify false information in Indonesian using an ensemble classifier that combines the n-gram method, term frequency-inverse document frequency, and passive-aggressive classifier method. The evaluation process was carried out using 5000 samples from Twitter social media accounts in this study. The testing process is carried out using four schemes by dividing the dataset into training and test data based on the ratios of 90:10, 80:20, 70:30, and 60:40. The inspection results show that our software can accurately detect hoaxes at 91.8%. We also found an increase in the accuracy and precision of hoax detection testing using the proposed method compared to several previous studies. The results show that our proposed method can be developed and used in detecting hoaxes in Indonesian on various social media platforms.

Item Type:	Article
Uncontrolled Keywords:	Hoax, Identification, Bahasa Indonesia, N-Gram, TF-IDF, Passive Aggressive Classifier,
Subjects:	T Technology > TA Engineering (General). Civil engineering (General)
Divisions:	Faculty of Engineering
Depositing User:	Library Umpo
Date Deposited:	21 Aug 2023 07:22
Last Modified:	21 Aug 2023 07:22
URI:	http://eprints.umpo.ac.id/id/eprint/11999

Actions (login required)

View Item