Blockchain-based barangay document management system with OCR data extraction (Record no. 37312)

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fixed length control field 02580nam a22002417a 4500
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control field ft8858
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control field 20251209142143.0
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fixed length control field 251209b ||||| |||| 00| 0 eng d
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Language code of text/sound track or separate title engtag
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Classification number T58 A28 2025
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Personal name Abubo, Katherine D.; Ramos, Eldrin Dave A.; Valencia, Faith A.
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Title Blockchain-based barangay document management system with OCR data extraction
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture .
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Date of production, publication, distribution, manufacture, or copyright notice c2025
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Other physical details Capstone Project: (Bachelor of Science in Information Technology) - Pamantasan ng Lungsod ng Maynila, 2025
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Formatted contents note ABSTRACT: This study introduces a Blockchain-Based Barangay Document Management System integrated with Optical Character Recognition (OCR) to address the longstanding inefficiencies of manual document handling in barangay offices. Traditional paper-based processes remain prone to delays, human error, and document loss, especially in the management of vital records such as barangay clearances and blotter reports. These challenges often compromise service delivery and raise concerns over data security and authenticity. To respond to this, the project aims to develop a secure and efficient web-based portal that integrates blockchain technology for tamper-proof storage and OCR for automated data extraction and verification. Using the Agile Scrum methodology, the development involved tools such as React.js for the frontend, and Node.js, Express.js and Google Cloud Vision API for the backend. Security was reinforced using AES-256 encryption, SHA-256 hashing, and Merkle Tree structures, ensuring the system’s data integrity and resistance to unauthorized modifications. The OCR component, tested through a word recognition benchmark, showed that Google Vision OCR accurately identified 19 out of 21 words, resulting in a 9.52% Word Error Rate (WER), significantly outperforming Tesseract OCR. The resulting system allows residents to request and upload documents online, while barangay officials can securely verify and manage these submissions. By combining automation, decentralization, and strong encryption protocols, the system reduces manual workload, enhances verification accuracy, and increases transparency in local governance. This research shows how emerging technologies can be used to modernize barangay operations and set a new standard for document management in public administration.
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Classification Filipiniana
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          Filipiniana-Thesis PLM PLM Filipiniana Section 2025-10-02   T58 A28 2025 FT8858 2025-12-09 2025-12-09 Thesis/Dissertation

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