Penerapan Rule-Based Keyword Matching dan OCR Tesseract untuk Validasi Dokumen Persyaratan pada Sistem Permohonan Pengujian ALSINTAN Berbasis Web

This study develops an automatic document validation feature for a web-based testing application used by UPTD BMSPP, West Sumatra, to process agricultural machinery testing applications. Previously, the system checked uploaded files only by format and size, not by content, so staff inspected every document manually and mismatched documents were detected only after processing. Here, “validation” means checking whether a document’s text matches its expected document type, it does not verify authenticity or legal validity. The study builds a model combining Optical Character Recognition (OCR) using the Tesseract engine with rule-based keyword matching for five document types. The model runs as a separate Python Flask microservice: it extracts text from digital PDFs using pdfplumber, applies Tesseract OCR to scanned documents and images, then compares the text with per-type keyword lists to return a real-time status. The system was developed using the Waterfall method and tested with black-box testing on six scenarios. Five of the six scenarios (83%) produced the expected results, this shows scenario conformity, not OCR recognition accuracy or classification accuracy on a broad document population. One scenario returned an error message that did not match the expected response for an unsupported file format, marking an area for improvement.