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Naufal Furqan Hardifa
Telkom University
Computer Science & IT

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Topic Classification of Islamic Questionand Answer Using Naive Bayes Classifier Naufal Furqan Hardifa; Kemas Muslim Lhaksmana; Jondri Jondri
Indonesia Journal on Computing (Indo-JC) Vol. 4 No. 2 (2019): September, 2019
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2019.4.2.346

Abstract

Topic classification is one of the most important components in an automatic Islamic question-answering system, which is capable of automatically providing the most relevant answers given a question about the Islamic issue. In our research, the Islamic question-answering system to be built collects existing Islamic questions and answers from trusted online Islamic consultation websites. To speed up the search for finding the appropriate answers, each Q & A entry should be classified into a topic. However, the question-answering system cannot directly adopt the topic classes provided by the online Islamic consultation websites, because different websites use different classifications. Since the number of Q & A entries could reach tenth thousands, an automatic topic classification method is required. In this paper, a naive Bayes classifier is implemented to classify Q & A entries. The classifier gives a satisfying result with 0.88 precision.
Co-Authors Jondri Jondri Kemas Muslim Lhaksmana