Small service businesses require efficient operational management and timely access to business information to support daily operations. Grandma Laundry Sumberkolak previously relied on manual transaction recording, handwritten receipts, conventional WhatsApp messaging, and manual sales recapitulation using a calculator, which made transaction handling less efficient and complicated sales report monitoring. This study aimed to design and implement a web-based laundry information system integrated with a WhatsApp Gateway and a chatbot for sales reporting. The study employed an applied research approach and used the Waterfall model, consisting of requirement analysis, system design, implementation, testing, and maintenance. The system was developed using Laravel, PHP, and PostgreSQL, with a WhatsApp Gateway service and a chatbot interface connected to an external GPT-4o-based large language model for natural-language access to sales data. The implemented system supported customer and service management, transaction processing, order status updates, automatic WhatsApp notifications, and interactive sales reporting. Functional testing and post-use user validation showed that the main system functions operated as expected; all 15 respondents gave affirmative responses to the seven post-use validation items, while four of five routine chatbot reporting prompts matched direct PostgreSQL reference results exactly. One routine prompt produced a partial result because of a timestamp-boundary issue in the generated SQL query. The findings indicate that the developed system can provide practical support for operational management, automated customer communication, and access to sales information in the studied laundry business
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