Shallots (Allium cepa var. ascalonicum) require effective irrigation to grow optimally. This research presents an IoT-based automatic watering system using Mamdani fuzzy logic method as watering control. The system uses two inputs, namely soil moisture and air temperature, and one output in the form of a watering pump. Soil moisture testing was conducted in three conditions: dry (0%-50%), moist (50%-70%), and wet (70%-100%). In addition, the tests also involved air temperature measurements categorized as cold (0°C-20°C), normal (20°C-32°C), and hot (32°C-50°C). The results show that the ideal humidity is between 55% and 58%. If the humidity exceeds 60%, the pump turns off to prevent the soil from getting too wet, and if it drops below 55%, the pump turns on as the soil starts to dry. Air temperature measurements showed consistent fluctuations throughout the day with small differences between the RTD PT-100 and Thermohygro Meter. The highest temperature occurred at 13:00 and the lowest at 18:00. This data is important for environmental management and system operations.
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