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All Journal IT JOURNAL RESEARCH AND DEVELOPMENT Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Building of Informatics, Technology and Science Zonasi: Jurnal Sistem Informasi Mitra Mahajana: Jurnal Pengabdian Masyarakat Jurnal J-PEMAS Indonesian Journal of Computer Science SATIN - Sains dan Teknologi Informasi
Edwar Ali
Jurusan STMIK Amik Riau
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Public Health Social Sciences

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Journal : IT JOURNAL RESEARCH AND DEVELOPMENT

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New Student Drug Tests at College Using Principal Component Analysis Method Agnes Chrisnalia; Edwar Ali; Mardainis Mardainis; Rahmiati Rahmiati
IT Journal Research and Development Vol. 6 No. 2 (2022)
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/itjrd.2022.7583

Abstract

Drugs are substances or illegal drugs that can endanger human life. Someone who consumes it in an inappropriate way will become dependent and even result in death. The physical characteristics of people who use drugs vary, but the more obvious characteristics are on the faces of drug users such as red eyes, stiff facial muscles, dark spots, pupils susceptible to light, sunken face shape, and dullness. The lack of physical characteristics of drug users due to similarities with other diseases makes it difficult for people to recognize them initially. However, for users whose face data has been tracked by the National Narcotics Agency, the facial data is stored in the dataset. This research was conducted with the aim of building a system that can detect and recognize prospective students whether they have ever been included in drug users recorded in the National Narcotics Agency dataset or not as one of the requirements for new student admissions to universities. The system built using the Principal Component Analysis method to process and extract images of the physical characteristics of drug users through the facial image data of drug users stored in the dataset. If the detected face has similarities with the characteristics in the dataset, it is necessary to suspect that the detected face is a drug user. The results of this study are the system is able to detect the faces of drug users using the Principal Component Analysis method with an accuracy of 90% and it is hoped that with this research the system can be one solution in helping universities as an identification effort to minimize drug use so that it can be an additional identification tool which strengthens someone detected using drugs.
Co-Authors Adellia Meiriza Agnes Chrisnalia Agustin Asri - Asri -, Asri Didik Sudyana Efrizoni, Lusiana Fadliansyah Hasibuan Fika Ayu Lestari Hamdani - Hengki Setiawan Herwin Herwin, Herwin Junadhi Junadhi Koko Harianto Mardainis Muhammad Azmi Nova Indriyani Rahmaddeni Rahmaddeni Rahmiati Sharon - Sharon -, Sharon Susandri -, Susandri Susandri, Susandri Susanti, Susanti Triyani Arita Fitri Unang Rio Yansyah Saputra Wijaya