An Indonesian Hoax News Detection System Using Reader Feedback and Naïve Bayes Algorithm

Hoax news in Indonesia spread at an alarming rate. To reduce this, hoax news detection system needs to be created and put into practice. Such a system may use readers’ feedback and Naïve Bayes algorithm, which is used to verify news. Overtime, by using readers’ feedback, database corpus will continu...

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Published inCybernetics and information technologies : CIT Vol. 20; no. 1; pp. 82 - 94
Main Authors Zaman, Badrus, Justitia, Army, Sani, Kretawiweka Nuraga, Purwanti, Endah
Format Journal Article
LanguageEnglish
Published Sofia Sciendo 01.03.2020
De Gruyter Brill Sp. z o.o., Paradigm Publishing Services
Subjects
Online AccessGet full text
ISSN1314-4081
1311-9702
1314-4081
DOI10.2478/cait-2020-0006

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Abstract Hoax news in Indonesia spread at an alarming rate. To reduce this, hoax news detection system needs to be created and put into practice. Such a system may use readers’ feedback and Naïve Bayes algorithm, which is used to verify news. Overtime, by using readers’ feedback, database corpus will continue to grow and could improve system performance. The current research aims to reach this. System performance evaluation is carried out under two conditions ‒ with and without sources (URL). The system is able to detect hoax news very well under both conditions. The highest precision, recall and f-measure values when including URL are 0.91, 1, and 0.95 respectively. Meanwhile, the highest value of precision, recall and f-measure without URL are 0.88, 1 and 0.94, respectively.
AbstractList Hoax news in Indonesia spread at an alarming rate. To reduce this, hoax news detection system needs to be created and put into practice. Such a system may use readers’ feedback and Naïve Bayes algorithm, which is used to verify news. Overtime, by using readers’ feedback, database corpus will continue to grow and could improve system performance. The current research aims to reach this. System performance evaluation is carried out under two conditions ‒ with and without sources (URL). The system is able to detect hoax news very well under both conditions. The highest precision, recall and f-measure values when including URL are 0.91, 1, and 0.95 respectively. Meanwhile, the highest value of precision, recall and f-measure without URL are 0.88, 1 and 0.94, respectively.
Author Justitia, Army
Sani, Kretawiweka Nuraga
Zaman, Badrus
Purwanti, Endah
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Snippet Hoax news in Indonesia spread at an alarming rate. To reduce this, hoax news detection system needs to be created and put into practice. Such a system may use...
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SubjectTerms Hoax news
Indonesian news
Naïve Bayes
reader feedback.s
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Title An Indonesian Hoax News Detection System Using Reader Feedback and Naïve Bayes Algorithm
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