Klasifikasi Penyakit Padi berdasarkan Citra Daun Menggunakan Model Terlatih Resnet101

Classification of Rice Diseases based on Leaf Image Using Resnet101 Trained Model

  • Ulfah Nur Oktaviana Universitas Muhammadiyah Malang
  • Ricky Hendrawan Universitas Muhammadiyah Malang
  • Alfian Dwi Khoirul Annas Universitas Muhammadiyah Malang
  • Galih Wasis Wicaksono Universitas Muhammadiyah Malang https://orcid.org/0000-0002-8096-1762
Keywords: Classification, Disease, Paddy, Image, CNN, ResNet101


Rice is a staple food source for most countries in the world, including Indonesia. The problem of rice disease is a problem that is quite crucial and is experienced by many farmers. Approximately 200,000 - 300,000 tons per year the amount of rice attacked by pests in Indonesia. Considerable losses are caused by late-diagnosed rice plant diseases that reach a severe stage and cause crop failure. The limited number of Agricultural Extension Officers (PPL) and the Lack of information about disease and proper treatment are some of the causes of delays in handling rice diseases. Therefore, with the development of information technology and computers, it is possible to identify diseases by utilizing Artificial Intelligence, one of which is by using recognition methods based on image processing and pattern recognition technology. The purpose of this research is to create a Machine Learning model by applying the model architecture from Resnet101 combined with the model architecture from the author. The model proposed in this study produces an accuracy of 98.68%.


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How to Cite
Ulfah Nur Oktaviana, Ricky Hendrawan, Alfian Dwi Khoirul Annas, & Galih Wasis Wicaksono. (2021). Klasifikasi Penyakit Padi berdasarkan Citra Daun Menggunakan Model Terlatih Resnet101. Jurnal RESTI (Rekayasa Sistem Dan Teknologi Informasi), 5(6), 1216 - 1222. https://doi.org/10.29207/resti.v5i6.3607
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