Sistem Pembacaan Plat Nomor Otomatis untuk Kendali Akses Parkir Menggunakan YOLOv8 dan Tesseract
Abstract
Abstrak — Sistem parkir konvensional menghadapi tantangan dalam efisiensi dan keamanan, terutama dalam pencatatan data dan verifikasi akses manual. Untuk mengatasi masalah ini, dikembangkan sebuah simulasi sistem parkir cerdas berbasis Internet of Things (IoT) yang mengintegrasikan teknologi Automatic Number Plate Recognition (ANPR) sebagai mekanisme verifikasi utama untuk pembukaan palang otomatis. Sistem ini memanfaatkan model deteksi objek YOLOv8 untuk mengidentifikasi plat nomor kendaraan dan Tesseract OCR untuk mengekstrak karakternya. Pengujian dilakukan pada prototipe skala miniatur yang menggunakan Raspberry Pi 4 sebagai pusat kendali dan kamera webcam. Fokus pengujian meliputi akurasi pembacaan plat nomor format 7 dan 8 digit serta waktu pemrosesan yang dibutuhkan. Hasil simulasi menunjukkan bahwa sistem ANPR mampu menjalankan fungsinya secara efektif dalam lingkungan terkendali, dengan rata-rata waktu pemrosesan per plat nomor berada dalam kisaran 3-4 detik, meskipun akurasi bervariasi antara format plat. Analisis ini membuktikan kelayakan pendekatan berbasis machine learning sebagai fondasi teknis untuk sistem parkir otomatis yang efisien dan aman di masa mendatang. Kata kunci— ANPR, YOLOv8, Tesseract OCR, Raspberry Pi, Simulasi, Parkir Otomatis
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