The quality of water in aquaculture systems plays a critical role in maintaining the health andproductivity of aquatic organisms. Two key parameters affecting water quality are DissolvedOxygen (DO) and Total Suspended Solids (TSS), both of which fluctuate and can negativelyimpact fish survival rates. This study aims to design and evaluate a fuzzy logic-basedclassification system using the Mamdani method to assess water quality conditions based on DOand TSS values. The research employed a qualitative approach supported by simulation usingMATLAB software. The input variables were DO and TSS, while the output was theclassification of water quality into two categories: good and poor. The fuzzy inference systemwas constructed using membership functions and rule-based logic. The results showed that thesystem was capable of generating accurate and adaptive outputs, with a sample input of DO 9.04mg/L and TSS 235 mg/L producing an output value of 0.742, indicating good water quality.These findings demonstrate the effectiveness of the system in supporting water monitoring inaquaculture operations.
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