Building of Informatics, Technology and Science
Vol 3 No 3 (2021): December 2021

Expert System to Diagnose Diseases in Durian Plants using Naïve Bayes

Nugraha, Narantyo Maulana Adhi (Unknown)
Rahardian, Reva (Unknown)
Kridabayu, Adam Nur (Unknown)
Adhinata, Faisal Dharma (Unknown)
Ramadhan, Nur Ghaniaviyanto (Unknown)



Article Info

Publish Date
31 Dec 2021

Abstract

Durian is a fruit that is very popular and very easy to find throughout Indonesia. Durian fruit is a thorny fruit with a very pungent smell with a distinctive taste, and for some durian fans, the distinctive taste of durian is what makes durian unique compared to other fruits. However, it is unfortunate that the production and quality of durian fruit in Indonesia is currently still low due to the limited knowledge of farmers in caring for and maintaining durian plants from pests and diseases on durian plants. So far, in detecting pests and diseases, farmers still carry out pest and disease detection manually, and of course, this is very dependent on pest and disease observers/experts. For this reason, so that later the level of production and quality of durian in Indonesia can increase, we create an expert system to diagnose a disease in durian plants to help farmers overcome problems around pests and diseases commonly occur in durian plants. This study uses the Naïve Bayes method as a determinant of durian disease. The experimental results yield an accuracy of 82%, which indicates the proposed method is quite good in diagnosing durian disease.

Copyrights © 2021






Journal Info

Abbrev

bits

Publisher

Subject

Computer Science & IT

Description

Building of Informatics, Technology and Science (BITS) is an open access media in publishing scientific articles that contain the results of research in information technology and computers. Paper that enters this journal will be checked for plagiarism and peer-rewiew first to maintain its quality. ...