| dc.description.abstract | The existence of internet opens the gates to all kinds of information for all society levels. Unfortunately, not all of those information are good and useful ones, but could also be morally damaging such as pornography. Therefore, the danger of pornography could affect children that had use internet since their childhood. This requires a system that could identify and pick which website page that are worth seeing by them. Web page that contains pornography should be blocked right away.
This system is created by implementing the concept of information retrieval and classification method Naive Bayes, and also utilizing the existence of browser extension and web service. A web page would go through several phase of cleaning, tokenization, stop word, stemming, and grouping-weighting. All these steps will generate key words to be further processed by Naive Bayes calculation. This will ultimately reach a conclusion whether the page contains pornography or not. After that, the page that being categorized as porn will be blocked.
Based on the results of experiments performed, it was concluded that this system can classify and block pages that contain pornography. This study examined 120 pages, with 4 sets of training and testing. The average level of accuracy for all training and testing set is 89.58%. | en_US |
