<![CDATA[This study presents the development and implementation of an automatic irrigation system based on the Internet of Things (IoT) utilizing the Decision Tree algorithm. The system was applied in a hydroponic garden at Institut Shanti Bhuana Bengkayang. It employs a water level sensor to detect the volume of water, which is then processed using the Decision Tree classification to determine whether the irrigation valve should be opened or closed. Data collected from the sensor were analyzed both manually and programmatically to find the optimal threshold for decision-making. The system was integrated with the Blynk platform, allowing real-time monitoring and control. Testing was conducted over 7 days with 210 data points, and the classification model achieved an accuracy of 100%. The results indicate that the proposed system effectively automates irrigation, minimizes manual intervention, and provides a reliable solution for small-scale smart farming applications.]]>
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