The Development of Shallot Warehouse Management System Using Optical Character Recognition Technology

Abstract

The research on the development of a shallot warehouse management system using Optical Character Recognition technology. The objectives of the study are to: 1) develop a shallot warehouse management system using OCR technology. 2) evaluate the efficiency of the developed management system. 3) To assess user satisfaction with the shallot warehouse information service website. The system was developed with an automatic receipt data recording system using Tesseract OCR technology, which processes character data from receipt scans. The database management system uses MySQL and PHP programming language, a website was developed to provide services for customers to check information, shallot warehouse details, and process service fee payments. The experimental results revealed that, in the scanning tests, the suitable brightness adjustment range for image scanning was between -20 and +20, yielded an accuracy of 100%. The resolution adjustment experiment demonstrated that employing images at 1200 dpi achieved an accuracy rate of 99.33%. The system was able to recognize tilted characters at any angle with 100% accuracy. Scanning black-and-white receipts also achieved 99.33% accuracy. The processing time and data saving duration measured during the experiment averaged 12 seconds. The system also allows for data verification and correction before saving. The website development results demonstrated the ability to display detailed outputs such as quantity, weight, warehouse rental area, receipts, and performance evaluation results. The website's development effectiveness was rated as very good, with an average uses satisfaction score of 4.53 and a standard deviation of 0.76.