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All Journal Knowledge Engineering and Data Science Conference on Innovation and Application of Science and Technology (CIASTECH) Infotekmesin Jurnal Aplikasi Dan Inovasi Ipteks SOLIDITAS JPKMI (Jurnal Pengabdian Kepada Masyarakat Indonesia) Rainstek : Jurnal Terapan Sains dan Teknologi Journal of Mechanical and Electrical Technology Jurnal Bina Komputer Jurnal INFOTEL
Irawan, Novta Danyel
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Automotive Engineering Computer Science & IT Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Public Health Social Sciences

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Optimalisasi Sistem Pelanggaraan Lalu lintas Kendaraan Besar Menggunakan Algoritma Mobilnet-SSD dan Pengolahan Citra K-Nearest Neighbors (KNN) Okiandri, Diki; Irawan, Novta Danyel; Ardian, Yusriel; Nurdin, Shafiq; Siswoko, Muhammad Urfun Nuurrazzaq
Infotekmesin Vol 16 No 2 (2025): Infotekmesin: Juli 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i2.2743

Abstract

This study is motivated by the high rate of traffic violations involving large vehicles such as trucks and buses, particularly on city protocol roads where these types of vehicles are prohibited. Most existing e-ticketing (e-Tilang) systems are still unable to automatically detect large vehicles in real-time and simultaneously read their license plates accurately. This limitation represents a research gap that this study aims to address. The objective of this research is to develop an integrated system that automatically detects violations committed by large vehicles and reads their license plates. The system employs the MobileNet-SSD algorithm for detecting large vehicles from traffic video data and applies the K-Nearest Neighbors (KNN) method for license plate character recognition. Based on tests conducted on five traffic videos under various conditions (morning, afternoon, night), the system achieved a detection accuracy of 90% for large vehicles and an 80% accuracy in license plate recognition. The system performed optimally during daylight hours but showed reduced accuracy at night due to limited lighting conditions. The integration of these two methods has proven to be effective and feasible for real-time law enforcement systems, especially in areas with limited computational resources.
Co-Authors Arianti Kusumawardhani Djoko Adi Susilo Dwiyanto, Felix Andika I D, Riski Nur I Nyoman Gede Arya Astawa Muhammad Athoillah Okiandri, Diki Onny Setyawati Purnama, Ida Bagus Irawan Riski Nur Istiqomah Dinnullah Shafiq Nurdin Shafiq Nurdin Siswoko, Muhammad Urfun Nuurrazzaq Sutoko, Sutoko Wijono Wijono Wijono Wijono Yordano Dwi Yunan Bramasta Yunus E. P., Amak Yusriel Ardian