Skripsi

 KLASIFIKASI CITRA PORNOGRAFI BERDASARKAN WARNA KULIT MANUSIA DALAM RUANG WARNA HSV DENGAN ALGORITMA K-NEAREST NEIGHBOR.

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Penilaian

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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%

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2307003457	T103423	T1034232023	Central Library (Referens)	Available

Detail Information

Series Title

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Call Number

T1034232023

Publisher

Indralaya : Prodi Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2023

Collation

xv, 61 hlm.; Ilus,; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

005.740 7

Content Type

Text

Media Type

unmediated

Carrier Type

-

Edition

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Subject(s)

Prodi Teknik Informatika
Pemerosesan Data elektrinik

Specific Detail Info

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Statement of Responsibility

MURZ

Other version/related

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