<![CDATA[Precision agriculture is a modern approach that integrates information technology to improve productivity and efficiency in the agricultural sector. Drone technology, or unmanned aerial vehicles, has become an essential tool for real-time plant health monitoring with high accuracy. This study aims to theoretically analyze the utilization of drone technology in plant health monitoring within precision agriculture systems. The method used is a literature review, analyzing various scientific publications related to drone applications, multispectral sensors, image processing, and plant health data interpretation. The analysis results indicate that drone technology equipped with multispectral and hyperspectral sensors can detect plant stress, nutrient deficiencies, pest and disease outbreaks at early stages with an accuracy of 85-95 percent. Data processing using machine learning algorithms and vegetation indices such as NDVI, NDRE, and GNDVI provides precise spatial information for decision-making. The implementation of this technology can improve agricultural input efficiency by up to 30 percent and crop yield productivity by up to 20 percent. The conclusion of this study is that drone technology holds significant potential in transforming agricultural practices towards more precise, sustainable, and productive systems.]]>
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