The Empirical Study On Algorithm Optimization In Expert Systems For Diagnosing Rice Plant Diseases

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Keywords: Expert System, Forward Chaining, Diagnoses, Rice Diseases, Web-Based

Abstract

Rice is one of the most important cultivated plants for human survival. The activity of cultivating rice plants becomes a livelihood for most of these residents, so the success rate of the amount of rice harvested becomes very important because they depend on how much rice can be harvested, disease diagnosis is very important for farmers, this is very important to reduce economic losses due to diseases that cause crop failure. Therefore, when dealing with rice diseases, an expert is needed to make diagnoses or solutions to rice diseases. However, an expert does not know when to come to the village, and farmers also do not understand all rice diseases. Therefore, a web-based expert system application using the forward chaining method is proposed to represent an expert to help farmers diagnose and solve diseases of rice plants with existing symptoms.

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Author Biographies

Ahmad Habib, Universitas 17 Agustus 1945 Surabaya

Department of Informatics Engineering, Universitas 17 Agustus 1945 Surabaya

Muhamat Sun'an, Universitas 17 Agustus Surabaya

Department of Informatics Engineering, Universitas 17 Agustus 1945 Surabaya

Roenardi Koesdijarto, Universitas 17 Agustus 1945 Surabaya

Department of Informatics Engineering, Universitas 17 Agustus 1945 Surabaya

 
Sajiyo, Universitas 17 Agustus 1945 Surabaya

Department of Industrial Engineering, Universitas 17 Agustus 1945 Surabaya

 
Elsen Ronando, Kyushu Institute of Technology Japan

Kyushu Institute of Technology Japan

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Published
2024-02-01
How to Cite
[1]
A. Habib, M. Sunan, R. Koesdijarto, S. Sajiyo, and E. Ronando, “The Empirical Study On Algorithm Optimization In Expert Systems For Diagnosing Rice Plant Diseases”, intensif, vol. 8, no. 1, pp. 1-12, Feb. 2024.