<![CDATA[Achieving optimal growth and yield in hydroponic tomato farming demands strict control over nutrient composition and environmental factors. To support efficient physiological functions such as photosynthesis, transpiration, and nutrient uptake key parameters including nutrient solution pH, ambient temperature, and water levels must remain within specific thresholds. Relying on manual control frequently leads to delayed responses against environmental shifts, causing inconsistent plant performance. Consequently, this research focuses on developing an automated nutrient control system tailored for hydroponic tomatoes, leveraging Mamdani Fuzzy Logic embedded in an Arduino microcontroller. Input data from pH, temperature, water level, and light intensity sensors undergoes fuzzification, rule-based inference, and centroid defuzzification. Based on these processes, the system generates control signals to adjust fan speeds and solenoid valve durations, ensuring environmental stability. Experimental findings indicate that the proposed system adapts effectively to parameter variations, offering smoother control than traditional threshold-based methods. Ultimately, this Mamdani fuzzy-based approach significantly stabilizes the hydroponic environment while minimizing the need for manual intervention.]]>
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