<![CDATA[Distribution companies face significant challenges in securing electronic invoices, as PDF files are susceptible to unauthorized text extraction and manipulation. Prior solutions include SHA-256 digital signatures, and QR code-based verification. There are often require specialized tools, stable internet, or user intervention posing barriers for general trade customers with limited digital access. To address these limitations, this study proposes a hybrid e-invoicing method by converting invoices into image-based PDFs embedded with QR codes. This approach enhances document security, increases resistance to text manipulation, and ensures file sizes remain under 1 MB for smooth distribution via WhatsApp. A dataset of 1000 invoices was tested using OCR and FuzzyWuzzy string similarity to compare extractability between text-based and image-based formats. A composite score was calculated by combining file size and manipulation resistance metrics. Results show that image-based PDFs achieve a significantly higher score (0.595) compared to text-based PDFs (0.005), confirming their superiority in terms of size efficiency and data security. The findings demonstrate that this method provides a robust, low-cost, and scalable solution for secure invoice distribution in environments with limited infrastructure and technical literacy.]]>
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