The quality of citrus plants needs to be carefully monitored to improve the
production and quality of citrus fruits. Diseases that attack citrus leaves are one of
the factors contributing to the low quality of citrus plants. Laboratory tests or direct
visual inspection are the only methods available to classify citrus tree diseases.
More knowledge is needed to identify citrus plant diseases accurately to ensure
proper and effective control. A solution is required to classify citrus tree diseases,
particularly those affecting the leaves, to address concerns about the limited
knowledge of citrus farmers, especially new ones. This can be achieved by
implementing the K-Nearest Neighbor (KNN) algorithm using HSV feature
extraction with varying k values of 1, 3, 5, 7, and 9. The type of citrus plant used in
this study is the Borneo variety. Implementing the KNN algorithm with HSV feature
extraction successfully classified images of citrus leaf diseases, identifying their
causes and treatment methods. The accuracy achieved by implementing the KNN
algorithm with the best k value of 5 is 90%.