Astuti, Wiji (2024) Klasifikasi Hama Pada Citra Daun Jeruk Menggunakan Metode Glcm Dan K-nn. Other thesis, Universitas Islam Riau.

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Abstract

Citrus plants are fruit plants that originated in Asia (Foda et al., 2021). Until now, citrus is still a profitable fruit to be cultivated, therefore the quality of citrus plants needs to be considered in order to improve the quality and yield of good citrus. Factors that cause low citrus quality are pest attacks on the leaves of citrus plants. Leaves on plants are a process for photosynthesis, if the leaves are attacked by pests it will cause the inability to provide food for plant parts. Growth will be disrupted and will produce poor fruit. The pests that attack the leaves of citrus plants are Peliang caterpillars and scale lice. Therefore, a system is needed that can identify these pests. Image processing is a process used in identifying pests on citrus leaves. The identification process begins with the image acquisition stage using a camera, then prepsocessing resize and median on the image that has been acquired. Then the segmentation stage uses the HSV (Hue, Saturation, and Value) color space thresholding method. Then the image is extracted using the Gray Level CoOccurrence Matrix (GLCM) feature extraction method. After that, the results of the feature extraction are processed with the classification stage using the K-Nearest Neighbor (KNN) method. The results on the system using Single Decission Threshold testing in identifying images of citrus plant leaves get an accuracy rate of 82%. From the process that has been done on the identification of citrus plant leaves, it can be concluded that this system runs well to distinguish the types of pests that attack.

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