Citrus or lime plants are all flowering plants of the Citrus family of the Rutaceae tribe (the or... more Citrus or lime plants are all flowering plants of the Citrus family of the Rutaceae tribe (the orange-jerukan tribe). Citrus is a major fruit commodity that is widely cultivated by the people of Indonesia, especially in the Karo Regency. However, in the cultivation of citrus farmers often facing problems that can cause a decrease in production. Problems faced by citrus farmers include disease attacks as well pest. So we need a system that can identify diseases in citrus fruits. In this study the methods used are color histogram and gray level co-occurrence matrix (GLCM). Image of citrus fruit is used as input for image processing. The way this system works is to compare the samples of citrus fruits that will be examined with references in the database. The steps taken before identification are image processing, color feature extraction using color histogram and extraction of orange fruit texture using GLCM. Based on the test results in this study, it can be concluded that the system can identify the type of disease in citrus fruits with an highest accuracy of 83.33% and average accuracy of 75.50 %.
Citrus or lime plants are all flowering plants of the Citrus family of the Rutaceae tribe (the or... more Citrus or lime plants are all flowering plants of the Citrus family of the Rutaceae tribe (the orange-jerukan tribe). Citrus is a major fruit commodity that is widely cultivated by the people of Indonesia, especially in the Karo Regency. However, in the cultivation of citrus farmers often facing problems that can cause a decrease in production. Problems faced by citrus farmers include disease attacks as well pest. So we need a system that can identify diseases in citrus fruits. In this study the methods used are color histogram and gray level co-occurrence matrix (GLCM). Image of citrus fruit is used as input for image processing. The way this system works is to compare the samples of citrus fruits that will be examined with references in the database. The steps taken before identification are image processing, color feature extraction using color histogram and extraction of orange fruit texture using GLCM. Based on the test results in this study, it can be concluded that the system can identify the type of disease in citrus fruits with an highest accuracy of 83.33% and average accuracy of 75.50 %.
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Papers by zeheskiel sembiring
Keywords: Citrus fruit, Image Processing, Color Histogram, Gray Level Cooccurrence Matrix (GLCM), K-Nearest Neighbor (KNN).
Keywords: Citrus fruit, Image Processing, Color Histogram, Gray Level Cooccurrence Matrix (GLCM), K-Nearest Neighbor (KNN).