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All Journal METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi KOMPUTIKA - Jurnal Sistem Komputer Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK)
FAUZAN ABDILLAH
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Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering

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Journal : KOMPUTIKA - Jurnal Sistem Komputer

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Prototipe Sederhana Sistem Deteksi Kriminal Berbasis Internet Of Things Menggunakan Teknologi YOLOv5 Nurfal Aziz, Afris; Khoiriyah, Hani’atul; Abdillah, Fauzan; Wiryawan, I Gede
Komputika : Jurnal Sistem Komputer Vol 13 No 1 (2024): Komputika: Jurnal Sistem Komputer
Publisher : Computer Engineering Departement, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputika.v13i1.12217

Abstract

Crime is any action or thing carried out by an individual, group or community that violates the law or is a criminal act, which disturbs social balance or stability in society. One of the tools used to monitor security in various places such as homes, offices and other public places is Closed-Circuit Television (CCTV). However, even though many CCTVs have been installed, many crimes still occur due to limitations in monitoring and supervision by security officers. Therefore, developing a crime detection system on CCTV using deep learning methods is considered important to increase security and reduce crime rates. The aim of a criminal detection system is to increase security and prevent criminal acts in a certain area or place. The technology used is YOLOv5 and is supported by Internet of Things-based hardware. The system succeeded in detecting violence objects 92% of the time and robbery 91% of the time in initial testing without background. In the second background test, the system succeeded in detecting violence objects 93% of the time and robbery 53% of the time. The system succeeded in detecting violence objects 91% of the time and robbery 83% of the time in real-time testing.
Co-Authors Amin, Muhammad Yusril Atmadji, Ery Setiawan Jullev Aziz, Afris Nurfal Gumilang, Mukhamad Angga I Gede Wiryawan Khoiriyah, Hani’atul Lestari, Winda Budi Nurfal Aziz, Afris Sirojudin, Achmad