PEMANFAATAN YOLOV4 UNTUK DETEKSI PELANGGARAN HELM DAN MASKER SERTA IDENTIFIKASI PELAT NOMOR MENGGUNAKAN TESSERACT-OCR
DOI:
https://doi.org/10.30736/informatika.v7i2.873Keywords:
deteksi objek, pengenalan karakter, yolo, deep learningAbstract
Dunia sedang dilanda pandemi sehingga mengharuskan manusia memakai masker saat berada di luar ruangan. Dalam rangka mencegah persebaran virus dan memastikan ketertiban pengendara sepeda motor, penting bagi pengendara sepeda motor memakai helm dan masker secara bersamaan. Oleh sebab itu dibuatlah program yang dapat mendeteksi pelanggaran helm dan masker serta mendapatkan nomor plat pelanggar secara otomatis. penelitian ini menggunakan metode transfer learning YOLOv4 dan memanfaatkan Tesseract-OCR. YOLOv4 mampu mendeteksi objek helm, masker, sepeda motor dan plat dalam satu gambar. Dengan menggunakan dataset sejumlah 600 gambar menghasilkan 8 model, model dengan Mean Average Precision (mAP) tertinggi 93.38% dan F1-Score 0.77. model dengan F1-Score tertinggi 0.86 dengan mAP 88.78%. Dapat disimpulkan bahwa model dengan F1-Score tertinggi lebih baik dalam deteksi dan klasifikasi objek. Sementara pelatihan model Tesseract membantu meningkatkan identifikasi karakter pelat nomor.
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