<![CDATA[Maize (Zea mays), as one of Indonesia’s primary agricultural commodities, often suffers from diseases such as stem rot, leaf spot, and fungal infections, which reduce its productivity. This study focuses on designing a user interface for a maize disease detection system using the User-Centered Design (UCD) approach—an approach that remains rarely applied in the context of agricultural AI systems. Unlike previous studies that applied UCD in areas such as waste management, web interface audits, and educational websites, this study emphasizes the integration of UCD into an AI-based crop disease detection tool. The design process followed the standard UCD stages understanding the context of use, specifying user requirements, developing design solutions, and evaluating the design. The interface was developed using Figma and evaluated through the System Usability Scale (SUS) method. The evaluation yielded a SUS score of 79, categorized as "Good" (Grade B), indicating a high level of usability and user satisfaction. This study contributes to expanding the implementation of user-centered design in the agricultural sector, offering a novel and practical approach to enhancing AI system adoption among end-users in farming.]]>
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