Proceedings of the 1st International Conference on Neural Networks and Machine Learning 2022 (ICONNSMAL 2022)

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Classification of Disease in Rice Plant Leaves Using the Method Convolutional Neural Networks

Authors
Laila Badriyatuz Zahro1, Dafik2, 3, Ika Hesti Agustin1, *, Zainur Rasyid Ridlo2, 4
1Department of Mathematics, University of Jember, Jember, Indonesia
2PUI-PT Combinatroics and Graph, CGANT, University of Jember, Jember, Indonesia
3Department of Mathematics Education Postgraduate, University of Jember, Jember, Indonesia
4Department of Science Education, University of Jember, Jember, Indonesia
*Corresponding author. Email: ikahesti.fmipa@unej.ac.id
Corresponding Author
Ika Hesti Agustin
Available Online 22 May 2023.
DOI
10.2991/978-94-6463-174-6_16How to use a DOI?
Keywords
rice plant diseases; convolutional neural networks; image classification
Abstract

Rice plant disease is one of the factors causing high losses due to crop failure. Plant-disturbing organisms often attack rice plants, especially on the leaves. This can damage rice plants and cause crop failure. Manual diagnostic activities on rice plant leaves will help identify and classify the types of diseases suffered by rice plant leaves. This study aims to be able to detect diseases that occur in the leaves of rice plants using the Convolutional Neural Network (CNN) method. Convolutional Neural Network is one method that is quite effective for image classification. Image will go through the Pre-Processing, Feature Extraction and Evaluation processes. The dataset used is RiceLeafs Diseases from kaggle with a total of 3000 samples of rice leaf images, 2100 images for training and 300 images for testing. In our research we used 3 different epoch numbers to find the value that produces the highest accuracy. Based on the research, it was found that 75 epochs had the highest accuracy value namely 85.67%.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 1st International Conference on Neural Networks and Machine Learning 2022 (ICONNSMAL 2022)
Series
Advances in Intelligent Systems Research
Publication Date
22 May 2023
ISBN
978-94-6463-174-6
ISSN
1951-6851
DOI
10.2991/978-94-6463-174-6_16How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Laila Badriyatuz Zahro
AU  - Dafik
AU  - Ika Hesti Agustin
AU  - Zainur Rasyid Ridlo
PY  - 2023
DA  - 2023/05/22
TI  - Classification of Disease in Rice Plant Leaves Using the Method Convolutional Neural Networks
BT  - Proceedings of the 1st International Conference on Neural Networks and Machine Learning 2022 (ICONNSMAL 2022)
PB  - Atlantis Press
SP  - 195
EP  - 216
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-174-6_16
DO  - 10.2991/978-94-6463-174-6_16
ID  - Zahro2023
ER  -