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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
Publisher : Pusat Penelitian, Pengembangan, dan Pemberdayaan Masyarakat (P4M) Politeknik Manufaktur Bandung (Polman Bandung)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.48182/jtrm.v7i1.193

Abstract

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.