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All Journal KOMPUTIKA - Jurnal Sistem Komputer Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK)
Khoiriyah, Hani’atul
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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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.
Sistem Deteksi Kekerasan Real-Time menggunakan YOLOv5 untuk Keamanan Publik Abdillah, Fauzan; Khoiriyah, Hani’atul; Aziz, Afris Nurfal; Wiryawan, I Gede
Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) 2024: SNESTIK IV
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/p.snestik.2024.5861

Abstract

Kekerasan, baik secara fisik, mental, maupun emosional, merupakan masalah serius yang menghambat pemenuhan hak asasi manusia dan kesempatan untuk berkembang. Penelitian ini mengusulkan solusi untuk mendeteksi kekerasan dengan memanfaatkan algoritma YOLOv5. Proses pengembangan mencakup pengumpulan dataset, pelatihan model, pengujian, dan analisis model. Dataset terdiri dari 6.000 gambar yang dilabeli sebagai "violence" dan “normal”, yang dibagi menjadi train, valid, dan test set. Model dilatih dengan 50 epoch, menunjukkan akurasi deteksi sebesar 73.08%. Evaluasi model menggunakan Confusion Matrix menunjukkan performa yang memadai, dengan 357 gambar violence terdeteksi dengan benar (True Positive). Namun, ada 160 gambar normal yang salah diklasifikasikan sebagai violence (False Positive). Model juga memiliki recall sekitar 86.55% untuk violence dan 80.26% untuk normal. Temuan ini menunjukkan potensi besar solusi ini dalam mendukung upaya pencegahan kekerasan dan pemantauan situasi secara real-time, serta memberikan kontribusi dalam menciptakan lingkungan yang lebih aman dan responsif terhadap kekerasan.
Co-Authors Aziz, Afris Nurfal FAUZAN ABDILLAH I Gede Wiryawan Nurfal Aziz, Afris