Design and Implementation of IoT and Smart Farming Hydroponic Systems for Adaptive Nutrition and pH Regulation in Strawberry Cultivation

Strawberry cultivation in Batu City, especially in the Bonkopi strawberry picking tourism area, faces challenges due to high rainfall that accelerates fruit decay and reduces productivity. Strawberry plants are highly sensitive to fluctuations in nutrient concentration and pH, which directly affect leaf color, root health, and nutrient absorption, leading to reduced fruit quality. To overcome the dependence on unstable soil conditions caused by excessive rainfall, this study proposes a smart hydroponic farming system integrating the Internet of Things (IoT) and Artificial Intelligence (AI) for adaptive nutrient and pH regulation. The IoT layer measures environmental (temperature and humidity) and hydroponic parameters (pH and electrical conductivity) in real time, controls actuators, and transmits data to the cloud for storage and visualization via the Blynk platform. The AI layer analyzes sensor data, predicts actuator responses using a Decision Tree Multi-Output model, and detects anomalies through an Isolation Forest algorithm, enabling adaptive and accurate nutrient delivery. Experimental results show that the regulation of nutrient and pH levels stabilizes the hydroponic medium, prevents leaf burn, stimulates the faster growth of stolons and flower buds, and accelerates fruit formation. The proposed system demonstrates that combining IoT and AI enables a reliable and intelligent hydroponic control system capable of maintaining strawberry plant health and improving overall productivity despite fluctuating environmental conditions.