Abstract
Water guava is a fruit that has many benefits. There are many types of water guava such as Leang, Citra, and Kaget. These types of water guava have some similarities in leaf shape, making it difficult for ordinary people to recognize the type of water guava plant. This study aims to make it easier for ordinary people to recognize the types of guava based on the texture of the leaves. The method used is the Gabor Filter and K-NN (K-Nearest Neighbor). Before extracting the leaf image data, a total of 150 leaf image datasets from each type of guava (Leang, Citra, Kaget) were converted to grayscale first and then extracted using a Gabor filter. Then classification is carried out with K-NN using the Gabor filter method and K-NN. The accuracy results obtained by combining the two methods are 93.34%.
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