Fuzzy Inference System to Improve Catfish Care in Bioflok Pools Based on Temperature and Water Quality - Analiah Fahlevy Yusuf; Zidan Febrian; Muhammad Fathurrahman; Rajwa Daffa Adyatama Yuristiawan; Steven Jona Duari Huta Balian; Dwi Yulinar Chairunisa; Agung Prayudha Hidayat (Journal of Applied Science, Technology & Humanities | JASTH, 2025)
The study explores the application of the Fuzzy Inference System (FIS) to improve the maintenance of clay (Clarias gariepinus) in Biofloc ponds, focusing on critical factors such as temperature and water quality. In the context of the efficiency of the biofloc system in water quality management, the study addresses the challenges posed by dynamic environmental conditions. Through a comprehensive gap analysis, the study identifies disparities between current research and the need for a specialized approach that integrates FIS for adaptive decision-making. The urgency stems from the limited coverage of previous research in addressing temperature dynamics and water quality. This research places itself in the research landscape by supporting and refining previous findings and introducing new FIS applications. The integration of Fuzzy Logic into bio floc management decision-making is new in this study. This research, supported by the latest literature from leading journals, emphasizes the significance and originality of its approach, contributing to sustainable and adaptive aquaculture practices.