The manual verification of motorcycle down payments at PT Banten Bakti Motor may cause delays in transaction confirmation, increase administrative workload, and create uncertainty for customers regarding their payment status. This study aims to develop an information system that automates motorcycle down-payment verification through a WhatsApp chatbot. The system was developed using the Prototyping method and a Docker-based microservices architecture by integrating WhatsApp HTTP API (WAHA), n8n for workflow orchestration, Google Gemini to support Natural Language Processing (NLP) and Optical Character Recognition (OCR), and Google Sheets as the data storage platform. Two primary mechanisms were implemented: an outbound workflow that proactively delivers notifications based on transaction data and an inbound workflow that receives customer responses and validates submitted payment evidence. Payment documents in image format are processed to extract essential information and subsequently matched with the company's transaction records. The implementation and testing results indicate that the system can handle multi -turn conversations, validate payment documents, automatically update transaction statuses, and provide customers with payment notifications. Therefore, the WhatsApp chatbot-based system can improve payment verification efficiency, reduce reliance on manual administrative processes, and provide customers with faster and clearer information regarding their payment status.
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