<![CDATA[Agriculture has an important role in Indonesia's economic development as one of the contributors to the state budget which continues to increase every year. In the post-covid 19 pandemic, there were problems that disrupted the economy, impacted on other fields such as agriculture, where the problem of the food crisis would become a problem for Indonesia if it was not handled properly. Agricultural land tends to be increasingly limited because they have to compete for various uses, while people working in agriculture in absolute terms continue to increase causing land ownership to become increasingly narrow. An effective pakcoy planting solution can be planted using hydroponic techniques, so there is a lot of interest from farmers to cultivate pakcoy plants but these plants are susceptible to disease. This research was conducted to detect disease in Pakcoy. The process of detecting Pakcoy disease focuses on knowing the disease of Rotten Pakcoy leaves (Phytoptora sp.) based on the Color Space Hue Saturation Value or HSV. Implementing a simple image using image processing taken using a webcam camera then processed on the Raspberry Pi 4 Model B for detection of pakcoy disease then displayed on the LCD16x2. Based on the research implementation process from start to finish it is able to work as expected. The accuracy of the pakcoy disease detection system resulted in an average accuracy value of 85% for 2 types of classes and an average computation time of 0.001213 seconds for 10 tests.]]>
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