Integrasi YOLOv8 dan EasyOCR untuk Deteksi dan Identifikasi Plat Nomor Kendaraan Indonesia

• Dika Putri Metalica
• 14220003

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ABSTRAK

Studi ini meneliti efektivitas YOLOv8 dan EasyOCR dalam deteksi dan pengenalan plat nomor kendaraan di Indonesia. Fokus utamanya adalah mengatasi tantangan ETLE dalam mengidentifikasi plat nomor dengan berbagai warna latar belakang. Metodologi mencakup pengumpulan dan augmentasi dataset. Model YOLOv8 dioptimalkan dengan batch size 16, 20 epochs, dan learning rate 0.001. Hasil evaluasi pada data training menunjukkan box_loss 1.074, mAP@0.5 0.947, precision 0.943, recall 0.953, F1-Score 1.00, dengan waktu training 0.559 jam, dan akurasi deteksi rata-rata di atas 85% untuk plat nomor single-class. EasyOCR menunjukkan akurasi tertinggi pada plat hitam (80.24%), diikuti plat kuning (69.40%), merah (69.26%), dan putih (64.21%). Kombinasi YOLOv8 dan EasyOCR efektif dalam berbagai kondisi, meskipun tantangan masih ada pada plat non-hitam.

Kata kunci: Plat Nomor, Yolov8, EasyOCR, Deteksi Karakter, Deep Learning

KATA KUNCI

Deep Learning,Deteksi Karakter

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