Open AccessAn Indonesian Hoax News Detection System Using Reader Feedback and Naïve Bayes Algorithm
Author(s) -
Badrus Zaman,
Army Justitia,
Kretawiweka Nuraga Sani,
Endah Purwanti
Publication year - 2020
Publication title -
cybernetics and information technologies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.272
H-Index - 17
eISSN - 1314-4081
pISSN - 1311-9702
DOI - 10.2478/cait-2020-0006
Subject(s) - hoax , computer science , indonesian , bayes' theorem , measure (data warehouse) , precision and recall , algorithm , recall , information retrieval , artificial intelligence , data mining , psychology , medicine , bayesian probability , philosophy , linguistics , alternative medicine , pathology , cognitive psychology
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.