IMPLEMENTASI OCR UNTUK DETEKSI PLAT GANJIL GENAP KENDARAAN MENGGUNAKAN METODE YOLOV8

Safnayanti, Aslamiyah (2025) IMPLEMENTASI OCR UNTUK DETEKSI PLAT GANJIL GENAP KENDARAAN MENGGUNAKAN METODE YOLOV8. Sarjana (S1) thesis, Universitas Islam 45.

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Abstract

Technological developments in the field of transportation have brought new solutions to traffic management, one of which is the odd-even system for regulating motor vehicles on the road. This study implements Optical Character Recognition (OCR) using the YOLOv8 method to detect vehicle license plates and automatically determine their odd-even status. The system utilizes Raspberry Pi 5 as the main controller, a webcam for image acquisition, and two OCR methods, EasyOCR and Tesseract, to read license plates. The results show that EasyOCR achieved a higher accuracy of 95.60% compared to Tesseract's 77.05%. Furthermore, the best image capture angle was found to be 75°, resulting in 100% detection accuracy. The system successfully controlled yellow and blue indicator lights with 100% accuracy to support the implementation of the odd-even policy.

Item Type: Thesis (TA, Skripsi, Tesis, Disertasi) (Sarjana (S1))
Contributors/Dosen Pembimbing,NIDN Dosen bisa diakses di LINK https://bit.ly/NIDNdosenunismabekasi:
ContributionContributors / Dosen PembimbingNIDN
UNSPECIFIEDFirasansi, Annisa0412108901
UNSPECIFIEDHasad, Andi0323047503
Keywords / Kata Kunci: YOLOv8, OCR, EasyOCR, Tesseract, Plat Nomor, Raspberry Pi
Subjects: Kendali/Kontrol
Sensor
Telekomunikasi
Faculty: Fakultas Teknik > Teknik Elektro S1
Depositing User: Mrs Aslamiyah Safnayanti
Date Deposited: 03 Sep 2025 08:54
Last Modified: 03 Sep 2025 08:54
URI: http://repository.unismabekasi.ac.id/id/eprint/8414

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