Implementation of Tesseract OCR for Automated Payment Validation in E-Commerce
Abstract
The rapid expansion of e-commerce in Indonesia has resulted in a significant increase in digital transactions, necessitating expedited and precise payment verification. Administrators at the SweetJab hijab e-commerce platform must manually verify bank transfer receipts, a process that is time-consuming and susceptible to errors. This study utilises Optical Character Recognition (OCR) with the Tesseract engine as a supplementary approach for verifying transfer payments on the SweetJab website. The methodology encompasses image preprocessing (resizing to 200%, converting to greyscale, and enhancing contrast), employing Tesseract OCR with PSM 6 and an LSTM model for character recognition, and utilising regular expressions (regex) to extract structured transaction data. We employed Black Box Testing and Character Error Rate (CER) computations on 40 preliminary test samples and 40 post-implementation samples to assess the system. The initial test demonstrated an accuracy of 89.5%, which increased to 92.5% upon complete system integration. This study demonstrates that OCR is an effective method for extracting information from payment receipts, while maintaining security through a final manual verification by the administrator.
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