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All Journal JOIV : International Journal on Informatics Visualization JIKO (Jurnal Informatika dan Komputer) JURNAL MEDIA INFORMATIKA BUDIDARMA Charity : Jurnal Pengabdian Masyarakat NUMBERS: Jurnal Pendidikan Matematika dan Ilmu Pengetahuan Alam Journal of Computer Engineering, Electronics and Information Technology
Devi Aprianti Rimadhani Agustini
Universitas Pendidikan Indonesia
Arts Humanities Chemistry Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Mathematics Physics Social Sciences Other

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Journal : JURNAL MEDIA INFORMATIKA BUDIDARMA

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Deteksi Konten Pornografi Menggunakan Convolutional Neural Network Untuk Melindungi Anak Dari Bahaya Pornografi Muhammad Taufik Dwi Putra; Mochamad Iqbal Ardimansyah; Devi Aprianti
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 4 (2022): Oktober 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i4.4793

Abstract

Education is one thing that must be arranged as early as conceivable in arrange to realize a quality era. When talking about education today, it cannot be separated from technology. Where we can see that technology has been used in various fields. In the field of education, one of them is the use of the internet network. However, the use of this technology has quite a bad side. Especially for elementary-level students or the age of children. That is the bad impact of exposure to pornography. Exposure to pornography is very dangerous and can damage children both psychologically and mentally. Therefore, it is important to minimize the risk of exposure to pornography. To overcome this, there are many methods that can be used. Like detecting pornographic content automatically and blocking it. One technique that can be developed to detect pornographic content is Artificial Neural Networks. However, so that the image input can be handled effectively, the model of the Artificial Neural Network has been varied into a Convolutional Neural Network (CNN) technique. So it has the ability to recognize objects for image data. The model built in this study was trained using a dataset that has been adapted to the definition of pornography in Indonesia. From the tests that have been carried out on the CNN model that was built, the best accuracy rate is 94.24%. in detecting images that fall into the category of pornographic content.
Co-Authors Ahmad Ali Alhafidz Ana Rahma Yuniarti Anugrah Adiwilaga Aulia Putri Cendekia Bhima Arya Daniswara Dastin Aryo Atmanto Jezzy Putra Munggaran Jorgha Akram Aryadi Kuswanto Kuswanto Maulana Taqy Mochamad Iqbal Ardimansyah Muhamad Rizki Wahyuddin Muhammad Taufik Dwi Putra Munawir Munawir Naufal Nurdiansyah Rifty Pradana Gunawan Wirmanto Suteddy Yahya Aliman Aidil Basith