Naïve bayes implementation into bahasa indonesia stemmer for content based webpage classification

Andreas, -- and Hartanti, Lusia Permata Sari (2016) Naïve bayes implementation into bahasa indonesia stemmer for content based webpage classification. Naïve bayes implementation into bahasa indonesia stemmer for content based webpage classification, 14 (11). pp. 8211-8223. ISSN 0972-7302-Jurnal Internasional SJR(2016): 0.123, Q4, H-Index: 19

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Abstract

A lot of information can be gathered by using internet technology. Internet may give out positive and negative impacts at once. There is a lot of content that not suitable to be consumed, especially for children, which is contain pornography. There are several ways have been done to block webpages containing pornography, but none has done it by reading the content. It is necessary to embed the machine learning role in the web browser so that the blocking process can be executed in real time. Blocking process performed by classifying web page based on its content into two groups, that is pornography or not. A good stemming process is needed in order to provide a good result of the web page reading. This study focuses on web pages in Bahasa Indonesia. Implementing Naive Bayes into Bahasa Indonesia stemmer algorithm in this study can classify web pages into several class with an accuracy of 84.03%.

Item Type: Article
Additional Information: Jurnal Internasional SJR(2016): 0.123, Q4, H-Index: 19
Uncontrolled Keywords: information retrieval, Naïve Bayes, web content filtering
Subjects: Engineering > Industrial Engineering
Divisions: Journal Publication
Depositing User: F.X. Hadi
Date Deposited: 02 Feb 2022 07:22
Last Modified: 02 Feb 2022 07:24
URI: http://repository.ukwms.ac.id/id/eprint/29216

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