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All Journal IAES International Journal of Robotics and Automation (IJRA) Indonesian Journal of Electronics and Instrumentation Systems Bulletin of Electrical Engineering and Informatics Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Indonesian Journal of Artificial Intelligence and Data Mining Jurnal Elektronika dan Telekomunikasi CYCLOTRON Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Multitek Indonesia : Jurnal Ilmiah Jurnal Elkolind : Jurnal Elektronika dan Otomasi Industri Jurnal Nasional Teknik Elektro dan Teknologi Informasi POLIGRID SinarFe7
Novendra Setyawan
Universitas Muhammadiyah Malang
Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering

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Journal : Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)

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Pemantauan Physical Distance Pada Area Umum Menggunakan YOLO Tiny V3 Mohammad Chasrun Hasani; Fadhila Milenasari; Novendra Setyawan
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 6 No 1 (2022): Februari 2022
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (731.977 KB) | DOI: 10.29207/resti.v6i1.3808

Abstract

Coronavirus disease in 2019 (Covid-19) is a phenomenon that become to the world concern because almost all countries experience the outbreak. One of attention to preventing the spread of Covid-19 is the physical distance in public areas. This study proposes human detection in public spaces by using image processing. The application of physical distance is intended to monitor the distance between people in public places. In this study, a human detection system is done by using the YOLO Tiny V3 method and the Euclidean algorithm to be developed to detect distances between humans. There are several stages in the research process: data collection, data preprocessing, data training, and physical distance detection. The system that has been designed can detect by getting an accuracy result of 78.43% for detecting human objects and an accuracy result of 87.82% for detecting distances between humans.
Co-Authors Ali Mukti Ali Mukti Amrul Faruq Amrul Faruq Amrul Faruq Anggar Kusuma Basri Noor Cahyadi Bella Retno Chatarina Umbul Wahyuni Diding Suhardi Dwi Nur Fajar Erdiaz Rakha Praditya Ermanu Azizul Ermanu Azizul Ermanu Azizul Hakim Ermanu Azizul Hakim Fadhila Milenasari Fitri Yakub Ghufron Wahyu Kurniawan Ghufron Wahyu Kurniawan Haris Rahmana Putra Ilyas Hamzah Alkatiri Indah Sulistiyowati Julianto Muchtadirul Hasan Khusnul Hidayat Komarudin Achmad Leonardo Kamajaya M. Irfan Machmud Effendy Mardiyah, Nur Alif Mardiyah, Nuralif Mas Nurul Achmadiah Mas Nurul Achmadiah Merinda Lestandy Mohammad Chasrun Hasani Muhammad Faris Pradana Muhammad Ikhwanul Khair Muhammad Irfan Muhammad Nasar Nasihol Fattah Noor Cahyadi, Basri Norazizah Nur Alif Mardiyah Nur Kasan, Nur Nuralif Mardiyah Nuralif Mardiyah Nurhadi Nurhadi Nurhadi, Nurhadi Nurul Achmadiah, Mas Rahayu Pandunengsih Retno, Bella Risdhayanti, Anindya Dwi Syachbani Amin Hidayat Syafaah, Lailis Syafaah, Lailis Tamadar Al Ghufran Yudawan Hidayat Zulfatman Zulfatman