The rapid development of information technology has significantly impacted the business world, including Micro, Small, and Medium Enterprises (MSMEs). However, business actors, particularly in the catfish farming sector, often face challenges in accessing broader markets and improving operational efficiency. This study aims to develop LeleQue, a web-based information system designed to efficiently support the management of catfish farming businesses. By implementing the SDLC (Software Development Life Cycle) method, this research outlines the system development process, from needs analysis to system evaluation The LeleQue application is equipped with key features such as financial bookkeeping, inventory management, debt tracking, financial reports, and discussion forums. The findings indicate that LeleQue provides an integrated platform to meet the operational management needs of catfish farming businesses. Additionally, the application facilitates collaboration among farmers through its community forum. This study contributes to supporting MSME digitalization, particularly in the catfish farming sector, to enhance efficiency, productivity, and business competitiveness.

This study focuses on black-box testing of JivaJoy software, an online product stock management and ordering system. The primary goal of this research is to evaluate the functionality and performance of the system's key features, including profile management, CRUD operations for admin and customer accounts, product stock management, shopping cart, order management, and AI counseling. Black-box testing was applied to assess whether these features meet expected operational standards and user requirements without considering the internal code structure. The test results indicate that most features function as expected. However, some issues were identified related to input validation, particularly with email format, phone number length, file uploads, and product stock management. Additionally, the order management and AI counseling features showed deficiencies in error handling and input validation. Based on these findings, the study recommends improvements in input validation, product stock management, shopping cart functionality, and AI counseling systems to enhance the reliability and performance of the JivaJoy platform. These enhancements are essential to deliver more efficient, secure, and optimal services, ensuring better user experiences and customer satisfaction.