Deteksi dan Interpretasi Tulisan Tangan Bahasa Indonesia melalui Pemrosesan Citra dan Optical Character Recognition (OCR)

Bhaskoro, Susetyo Bagas
Pratama, Rizqi Aji
Darmawan, Shafa Aulia Hazim

JTRM (Jurnal Teknologi dan Rekayasa Manufaktur)
Vol 7 No 1 (2025): Volume: 7 | Nomor: 1 | April 2025

This research develops a handwriting recognition system using OCR based on DB_Resnet and CRNN_VGG16 pre-training architecture integrated with hardware such as Arduino Uno, stepper motor, infrared sensor, camera, and aluminum frame. The system is equipped with a web-based interface developed using Flask. The test shows an average text recognition accuracy of 51.70% with validation using the KBBI dataset. The results show the successful integration of OCR technology with hardware and software, which is expected to increase the efficiency of handwriting data processing.