<![CDATA[Water quality, particularly pH, temperature, and turbidity parameters, plays an important role in maintaining the health of ornamental fish in aquariums. Fluctuations in these parameters can cause physiological stress and even death in fish if not properly controlled. This study aims to design an Internet of Things (IoT)-based water quality monitoring and control system using the Mamdani type Fuzzy Inference System (FIS) method. The system utilizes pH, temperature, and turbidity sensors connected to an ESP32 microcontroller to acquire data and transmit it in real-time to a cloud-based platform. Sensor values are processed through fuzzification, inference using the MIN operator and MAX aggregation, then defuzzification using the centroid method to produce decisions on fish conditions in the categories of healthy, sick, or dead. Simulation results using MATLAB Fuzzy Logic Toolbox show that the system is capable of providing a more stable non-linear response compared to conventional threshold methods. The integration of IoT and fuzzy logic enables more adaptive, proportional, and effective control in maintaining water quality within the optimal range for ornamental fish]]>
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