Sistem Pakar Diagnosa Penyakit Pada Tanaman Padi (Oryza) Menggunakan Metode Naïve Bayes

Rice (Oryza) is an important commodity, but in the process of cultivation, farmers still lack understanding about the diseases that attack rice plants. Therefore, an artificial intelligence-based expert system is implemented to identify diseases in rice plants according to the reasoning of an expert. In this research, the expert system method used is naive bayes to represent 18 symptoms and 5 diseases in rice plants. Naive Bayes is used because it can provide a statement that a symptom that appears in a condition is not interdependent between one another, so it can be used separately to assess the possibility of a condition based on the symptoms that appear. The application designed in this research is web-based and built based on PHP programming language and Codeigniter framework. This research aims to identify rice diseases that can be accessed by farmers by only accessing the rice plant expert system website using the internet so that they can carry out early control and increase the productivity of rice plants and increase the quantity of crops. The accuracy results obtained from this expert system amounted to 93.3% of the 30 sample data tested with 28 appropriate or valid data and 2 inappropriate data. This level of accuracy can allow farmers to immediately identify rice plant diseases and take control measures.

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Publication Details

Journal
Jikom Jurnal Informatika dan Komputer
Published
2024-10-14
DOI
https://doi.org/10.55794/jikom.v14i2.206
Primary Topic
Edcuational Technology Systems
Type
article
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article

Sistem Pakar Diagnosa Penyakit Pada Tanaman Padi (Oryza) Menggunakan Metode Naïve Bayes

M Daffa Rizkyansyah, Indah Susilawati
Jikom Jurnal Informatika dan Komputer
Edcuational Technology Systems
article

Sistem Pakar Diagnosa Penyakit Pada Tanaman Padi (Oryza) Menggunakan Metode Naïve Bayes

M Daffa Rizkyansyah, Indah Susilawati
article en

Abstract

Rice (Oryza) is an important commodity, but in the process of cultivation, farmers still lack understanding about the diseases that attack rice plants. Therefore, an artificial intelligence-based expert system is implemented to identify diseases in rice plants according to the reasoning of an expert. In this research, the expert system method used is naive bayes to represent 18 symptoms and 5 diseases in rice plants. Naive Bayes is used because it can provide a statement that a symptom that appears in a condition is not interdependent between one another, so it can be used separately to assess the possibility of a condition based on the symptoms that appear. The application designed in this research is web-based and built based on PHP programming language and Codeigniter framework. This research aims to identify rice diseases that can be accessed by farmers by only accessing the rice plant expert system website using the internet so that they can carry out early control and increase the productivity of rice plants and increase the quantity of crops. The accuracy results obtained from this expert system amounted to 93.3% of the 30 sample data tested with 28 appropriate or valid data and 2 inappropriate data. This level of accuracy can allow farmers to immediately identify rice plant diseases and take control measures.

Jikom Jurnal Informatika dan KomputerVol. 14(2)
Universitas Mercu Buana Yogyakarta (ID)
Openalex Percentile: Top 83%
Edcuational Technology Systems
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