PENGENALAN CITRA PENYAKIT DAUN PADI DI INDONESIA MENGGUNAKAN METODE XCEPTION DAN INCEPTIONV3

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Published: May 9, 2025
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Rice leaf disease, image, Xception, InceptionV3
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Renaldy

Abstract

Rice is a staple food in Indonesia because almost all Indonesians consume rice from processed rice which becomes rice. In Indonesia there is a problem faced by farmers, namely bacterial leaf blight or rice leaf disease. This problem causes the photosynthesis function of rice leaves to be disrupted, therefore the purpose of this research is to recognize rice leaf disease from images using Xception and InceptionV3 methods. There are 3 rice leaf diseases that will be recognized including blast, blight, and tungro. From the accuracy of the two Convnet models is very good in predicting rice leaf disease, the Xception model has a higher accuracy than InceptionV3. Xception produces a validation accuracy of 98% and InceptionV3 produces a validation accuracy of 95%.

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Vol. 15 No. 2 (2020): Jurnal Komputer dan Informatika
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Articles
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This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

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