<![CDATA[Digital transformation has emerged as a strategic imperative for small and medium enterprises (SMEs) in emerging economies, yet the ornamental fish retail sector in Indonesia remains predominantly offline, constrained by limited digital infrastructure and high customer knowledge barriers. No prior identified study has implemented artificial intelligence (AI)-assisted consultation within a domain-specific ornamental fish e-commerce platform, and comprehensive security implementation combined with multi-layer testing has been largely absent in comparable SME web systems. This study presents the design, implementation, and evaluation of a web-based information system for Toko Oasis, an ornamental fish and aquascape SME in Surabaya, Indonesia, developed within a Design Science Research (DSR) paradigm following a structured Software Development Life Cycle (SDLC). The system integrates a configurable large language model (LLM) consultation module—supporting OpenAI GPT-4 and Google Gemini—that delivers domain-specific advisory on ornamental fish species selection, aquarium parameters, and aquascape design through natural language interaction. System development produced twelve Unified Modeling Language (UML) artifacts and was evaluated through a tri-layer testing protocol operationalized against the ISO/IEC 25010:2011 software quality model. Functional testing achieved a 100% pass rate across 24 use cases. Performance testing recorded a mean response time of 4.2 seconds under 25 concurrent users, within the defined threshold of 5 seconds. Usability evaluation yielded a mean System Usability Scale (SUS) score of 80.0, classified as Good. Security validation confirmed full compliance across HTTPS/SSL-TLS transport and AES-256 at-rest encryption domains. Comparative analysis against prior literature and analogous commercial platforms confirms that this system constitutes the first identified deployment of AI-assisted consultation in ornamental fish retail, contributing a replicable digitalization architecture for niche-market SMEs in developing economies.]]>
