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All Journal Jurnal Indonesia Sosial Teknologi eProceedings of Engineering
Musyaffa, Muhammad Aththar
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Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Social Sciences

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Implementation of YOLOv8 for Real-Time Cars Detection and Counters on Security Gate Areas Musyaffa, Muhammad Aththar; Sumaryo, Sony; Zamhuri, Azam
eProceedings of Engineering Vol. 11 No. 5 (2024): Oktober 2024
Publisher : eProceedings of Engineering

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Abstract

Abstrak — Deteksi dan penghitungan kendaraan di gerbangkeamanan sangat penting untuk manajemen lalu lintas dankeselamatan. Studi ini mengimplementasikan YOLOv8,algoritma deteksi objek berbasis jaringan saraf konvolusional,dalam sistem waktu nyata untuk deteksi dan penghitungankendaraan. YOLOv8 dipilih karena kecepatan dankeakuratannya, yang penting untuk aplikasi waktu nyata.Model ini dilatih selama 300 periode, menghasilkanpeningkatan signifikan dalam metrik evaluasi: Box_lossmenurun dari 0,874540 menjadi 0,336177, Obj_Loss dari0,336177 menjadi 0,301361, dan Cls_Loss dari 0,301361menjadi 0,529893. Presisi meningkat menjadi 0,529893, Recallmenjadi 0,612314, mAP_0,5 meningkat dari 0,586869 menjadi0,746705, dan mAP_0,5:0,95 meningkat dari 0,446080 menjadi0,531407. Pengujian menunjukkan 17 deteksi dengan akurasi100% dan 19 hitungan dengan akurasi 89%. Model ini jugadiuji dalam berbagai kondisi cahaya, termasuk skenario gelapdan terang, yang menunjukkan kinerja yang konsisten dan hasildeteksi yang andal. Studi ini menyimpulkan bahwa modelYOLOv8 yang dilatih mencapai kinerja deteksi yang tinggi.Implementasi waktu nyata menggunakan kamera CCTVterbukti efektif dalam berbagai kondisi pencahayaan, yangmengonfirmasi kekokohan dan keandalan model. Temuan inimenggarisbawahi potensi YOLOv8 untuk secara signifikanmeningkatkan efisiensi dan keamanan di area yang dipantau.Hasilnya memberikan landasan yang kuat bagi penelitian danpengembangan di masa mendatang, yang bertujuan untuk lebihmenyempurnakan dan memperluas penerapan YOLOv8 dalamberbagai skenario deteksi dan penghitungan waktu nyata. Kata Kunci — YOLOv8, Object Detection, Real Time Detection.
Application of OCR Technology for Vehicle License Plate Detection and Yolo V8 for Car Counting Muhammad Ridwan, Rizki; Musyaffa, Muhammad Aththar; Azis, Kurniawan; Sumaryo, Sony; Zamhuri, Azam
Jurnal Indonesia Sosial Teknologi Vol. 5 No. 9 (2024): Jurnal Indonesia Sosial Teknologi
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jist.v5i9.1378

Abstract

The development of urban mobility and the growth in the number of motorized vehicles have created significant security challenges in managing parking areas. In this context, the use of Automatic License Plate Recognition (ALPR) technology and object detection emerges as a potential solution. Through the implementation of a smart camera system equipped with number plate detection and object detection, this research aims to reduce the risk of human error in recording parking data and prevent illegal parking. In answering this problem, this research offers a solution in the form of developing a smart camera system that is able to detect the presence of vehicles and recognize number plates with a high level of accuracy. Through the integration of ALPR and object detection, this system is expected to be able to overcome obstacles that arise in parking management, increase efficiency, and effectively prevent illegal parking. The implementation of automatic barriers, access cards and integrated CCTV monitoring will further strengthen the security of the parking area. With the research results, the proposed smart camera system succeeded in achieving vehicle and license plate detection accuracy levels above 90%. The quantitative and qualitative data collected supports the effectiveness of this solution in improving parking management and parking area security. In conclusion, this research makes a positive contribution in facing security challenges in cities through the use of advanced technology, opening up the potential for widespread application in the context of continuously developing urban mobility.
Co-Authors Azis, Kurniawan Muhammad Ridwan, Rizki Sony Sumaryo Zamhuri, Azam