This research focuses on the development of a water quality monitoring and improvement system tailored to the needs of Koi fish farmers, utilizing the Design Thinking (DT) approach. By leveraging both qualitative and quantitative research methods, the study identifies critical requirements and pain points in Koi fish farming and proposes a technological solution that integrates real-time data monitoring, automated water quality adjustment, and behavior analysis through a mobile application. This study aims to evaluate the performance of a water quality monitoring application, utilizing a Line chatbot as the primary communication tool for users. The application’s efficiency was assessed by three experts, with results indicating an excellent performance level, achieving 83.33% efficiency. In addition, user testing among the general public revealed a high level of satisfaction with the system, with an overall satisfaction score of 4.37 and a standard deviation (S.D.) of 0.75, classified as very good. The findings suggest that this application holds significant potential for real-world implementation. Recommendations for future development include enhancing the application by integrating modern design principles and staying abreast of emerging technologies. These improvements will ensure that the system remains efficient and responsive to user needs in the long term.