Catha Saintifica
Vol 3 No 1 (2025): May 2025 Article-in-Press

Expert System for Diagnosing Red Bean Plant Disease using Naïve Bayes Method

Mu'iz, Ngivanul (Unknown)
Sibyan, Hidayatus (Unknown)
Mahmudati, Rina (Unknown)



Article Info

Publish Date
09 Jun 2025

Abstract

Innovation in the development of various kinds of technology in various fields and fast sources of information, the use of these developments is used to overcome various challenges that arise, including in the field of agriculture. The main factor of problems that are often faced by farmers is in identifying diseases such as in plants including kidney bean plants, the main cause of the problem is the lack of knowledge about the disease, the absence of an expert in the field, and there is no expert system for diagnosing kidney bean plant diseases. The naïve bayes method is a method of calculation to determine a possibility, The implementation of the naïve bayes method in this expert system is carried out to determine the diagnosis of kidney bean disease based on kidney bean information, such as symptom data and emerging disease data. Determining the diagnosis of a disease from the calculation of the naïve Bayes method is based on the highest probability of disease diagnosis. Building an expert system for diagnosing diseases of red beans based on websites is used to assist farmers in diagnosing diseases and finding solutions based on the symptoms that arise. The results of this expert system test, taken from the system test on experts, obtained an accuracy score of 90%. This research produces efficient and easily accessible digital tools, which play a role in supporting food security and increasing farmers' productivity through a faster and more accurate disease diagnosis process.

Copyrights © 2025






Journal Info

Abbrev

catha

Publisher

Subject

Civil Engineering, Building, Construction & Architecture Computer Science & IT Education Energy Industrial & Manufacturing Engineering

Description

Catha Saintifica Journal, Journal of Creativity and Technology Innovation Research (ISSN: 30318211), is a communication and publication media for research results, creativity, product development and innovation, containing scientific articles in the form of research results in the fields of ...