AKBAR, MUHAMMAD RIZKI and Rini, Dian Palupi and Miraswan, Kanda Januar (2022) KLASIFIKASI CITRA PORNOGRAFI BERDASARKAN WARNA KULIT MANUSIA DALAM RUANG WARNA HSV DENGAN ALGORITMA K-NEAREST NEIGHBOR. Undergraduate thesis, Sriwijaya University.
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Abstract
People can accidentally stumble on pornographic content on internet, not to mention one can purposely search for it. Large number of criminal cases related to sex crimes, most of the perpetrators claim to be influenced by pornographic content. Digital images that are accessed from the internet cannot be separated from one of the media that could contain pornography, for this reason a system is needed that can determine which images are pornographic or not. In this study, the method uses is dominance of human skin color presented on an image in Hue, Saturation, Value (HSV) color space. After getting the percentage number of skin area in an image, then the K-Nearest Neighbor classifiers is used on unlabeled data to determine the nearest distance from sorted labeled data to classify the image is porn or not. The test results of the software obtained using the value of k = 3 have an accuracy of 80% and a precision of 84%.
Item Type: | Thesis (Undergraduate) |
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Subjects: | Q Science > Q Science (General) > Q1-295 General Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation. T Technology > TR Photography > TR1-1050 Photography |
Divisions: | 09-Faculty of Computer Science > 55201-Informatics (S1) |
Depositing User: | Muhammad Rizki Akbar |
Date Deposited: | 16 May 2023 08:16 |
Last Modified: | 16 May 2023 08:16 |
URI: | http://repository.unsri.ac.id/id/eprint/103423 |
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