This research holds high urgency, especially in the context of modern agriculture facing various challenges. In reality, the use of water and energy in conventional farming is often inefficient. Manual watering does not always align with the actual needs of the plants and causes water wastage. The same goes for the use of non-automated fans. This causes temperature instability, which should ideally be between 25-30°C, and soil moisture, which should ideally be 60-80%. This can hinder melon growth. The objective of this study is to create an IoT prototype using ESP32, DHT22, soil moisture sensor, and relay for automatic pump/fan control. Through the Borg and Gall research development method with Telegram monitoring, the result achieved melon growth of 130.5 cm with the ESP32 IoT system. Meanwhile, the melon growth without using the ESP32 IoT system was 82.5 cm. This research contributes to informatics through a low-cost adaptive system with potential for Machine Learning integration to predict water needs and disease risks in precision farming.
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