Proceedings of the International Conference on Applied Science and Technology on Engineering Science 2023 (iCAST-ES 2023)

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Expert System For Diagnosing Diseases In Rice Plants

Authors
Zaroh Khoerunisa1, *, Linda Perdana Wanti2, Oman Somantri2, Agus Susanto3, Ratih Hafsarah Maharani2
1Computer and Business, Cilacap State Polytechnic, Cilacap, Indonesia
2Cybersecurity Engineering, Cilacap State Polytechnic, Cilacap, Indonesia
3Multimedia Engineering Technology, Cilacap State Polytechnic, Cilacap, Indonesia
*Corresponding author. Email: zarohkhoerunisa.stu@pnc.ac.id
Corresponding Author
Zaroh Khoerunisa
Available Online 17 February 2024.
DOI
10.2991/978-94-6463-364-1_61How to use a DOI?
Keywords
Component; Expert System; Disease; Rice Plants; Certainty Factor; Waterfall
Abstract

Rice plants play a crucial role in satisfying human dietary requirements. However, they are vulnerable to diseases and various factors that can negatively impact crop yields and grain quality. Consequently, it is imperative to possess a comprehensive understanding of rice plant care and effective farming techniques to enhance rice production. This study addresses the challenges posed by limited knowledge about rice plant diseases and suboptimal practices observed in Gapoktan, located in the Ajibarang District, Banyumas Regency. The proposed solution involves the creation of a website-based expert system utilizing the Waterfall development methodology. This system is designed using the PHP programming language, managed by the MySQL database, and implemented with the Laravel framework. To tackle uncertainties during decision-making, the system employs the certainty factor method. The primary objective of this expert system is to expedite the diagnosis of rice plant diseases, facilitate farmer decision-making, minimize losses, and augment crop yields. The research findings indicate an average index score of 92% for each questionnaire item, signifying a highly favorable evaluation of the developed expert system.

Copyright
© 2024 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 International Conference on Applied Science and Technology on Engineering Science 2023 (iCAST-ES 2023)
Series
Advances in Engineering Research
Publication Date
17 February 2024
ISBN
10.2991/978-94-6463-364-1_61
ISSN
2352-5401
DOI
10.2991/978-94-6463-364-1_61How to use a DOI?
Copyright
© 2024 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  - Zaroh Khoerunisa
AU  - Linda Perdana Wanti
AU  - Oman Somantri
AU  - Agus Susanto
AU  - Ratih Hafsarah Maharani
PY  - 2024
DA  - 2024/02/17
TI  - Expert System For Diagnosing Diseases In Rice Plants
BT  - Proceedings of the International Conference on Applied Science and Technology on Engineering Science 2023 (iCAST-ES 2023)
PB  - Atlantis Press
SP  - 659
EP  - 672
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-364-1_61
DO  - 10.2991/978-94-6463-364-1_61
ID  - Khoerunisa2024
ER  -