AQUARA: Development of an AI-Assisted Integrated Web and Mobile Digital Platform for Fisheries Information Services and Aquaculture Business Analysis - Nur Budi Nugraha; Rendi Rendi; Fauzan Ishlakhuddin (Politeknik Negeri Batam, 2026)
Fish farmers in Indramayu Regency face difficulties in accessing fisheries information, evaluating aquaculture business feasibility, and communicating with the local fisheries authority because existing digital services are fragmented across multiple platforms. This study aims to develop AQUARA, an integrated web and mobile based platform that combines fisheries information, government services, aquaculture business analysis, discussion forums, a fish farmer directory, and AI assisted digital consultation. The platform was developed using a Research and Development (R&D) approach consisting of requirement analysis, system design, platform development, testing, and evaluation. System functionality was verified through Black Box Testing, non functional aspects were examined through performance, security, and compatibility testing, and usability was evaluated using the System Usability Scale (SUS). The testing results confirmed that all implemented features operated according to the specified requirements, the platform demonstrated acceptable response time, role based access control, and encrypted authentication, and it achieved a SUS score of 82.7 (Grade A), indicating excellent usability and high user acceptance. The integration of automated business feasibility analysis and the Dr. Fisho AI computer vision based preliminary fish disease detection feature within a single platform provides a practical solution for supporting the digital transformation of the aquaculture sector. The proposed platform improves information accessibility, supports business decision making, and strengthens collaboration among fish farmers and fisheries stakeholders.