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General Information
    • ISSN: 2010-3751
    • Frequency: Bimonthly (2012-2016); Quarterly (Since 2017)
    • DOI: 10.18178/IJFCC
    • Editor-in-Chief: Prof. Mohamed Othman
    • Executive Editor: Ms. Cherry L. Chan
    • Abstracting/ Indexing: Google Scholar,  Crossref, Electronic Journals LibraryEI (INSPEC, IET), etc.
    • E-mail:  ijfcc@ejournal.net 
Editor-in-chief
Prof. Mohamed Othman
Department of Communication Technology and Network Universiti Putra Malaysia, Malaysia
It is my honor to be the editor-in-chief of IJFCC. The journal publishes good papers in the field of future computer and communication. Hopefully, IJFCC will become a recognized journal among the readers in the filed of future computer and communication.
IJFCC 2017 Vol.6(4): 153-157 ISSN: 2010-3751
DOI: 10.18178/ijfcc.2017.6.4.509

Webpage Classification Using Naïve Bayes Classifier and Information Retrieval Method to Block the Pornography Contents

Andreas and Lusia Permata Sari Hartanti
Abstract—The need of information is such magnitude. It would trigger advances in information technology. Many things can be done by using the internet. The main objective that people use the Internet is to find the information. Unfortunately, not all the information available on the internet it is true and good consumed. There are plenty of information on the internet which is a hoax and contains elements that are contrary to morals and ethics such as terrorism, racism, and pornography. Thus, it required a strong faith and knowledge to be able to sort the incoming information. Due there are many children who also use the internet and conditions where the parents cannot supervise the activities of their children continuously, it would require an application that is embedded in the web browser so that bad content can be blocked automatically. This article focuses on the research of handling pornographic content on the text based webpages. It needed a smart application to be able to distinguish text that contains pornography. Thus, we are implementing artificial intelligence into our research by applying Naive Bayes and information retrieval method. As a result, the application is able to block 88.02% of the pornographic content.

Index Terms—Information retrieval, pornography, smart system, web content filtering.

Andreas is with Universitas Pelita Harapan Surabaya, Indonesia (e-mail: andreas.jodhinata@uph.edu).
Lusia Permata Sari Hartanti is with Universitas Pelita Harapan Surabaya, Indonesia (e-mail: lusia.hartanti@uph.edu).

[PDF]

Cite: Andreas and Lusia Permata Sari Hartanti, "Webpage Classification Using Naïve Bayes Classifier and Information Retrieval Method to Block the Pornography Contents," International Journal of Future Computer and Communication vol. 6, no. 4, pp. 153-157, 2017.

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