Use of an expert system to diagnose and provide solutions for pests and diseases in hydroponic mustard plants using certainty factor and forward chaining methods
Author Identifier
Ferry Jie: https://orcid.org/0000-0002-6287-8471
Document Type
Conference Proceeding
Publication Title
ICSINTESA 2024 - 2024 4th International Conference of Science and Information Technology in Smart Administration: The Collaboration of Smart Technology and Good Governance for Sustainable Development Goals
First Page
523
Last Page
527
Publisher
IEEE
School
School of Business and Law
RAS ID
77624
Abstract
Mustard greens are a vegetable that is very popular with people, especially hydroponic mustard greens, which appear fresher. However, like other vegetables, mustard greens grown hydroponically are also susceptible to pests and diseases, which can cause the vegetables to lose their freshness and may even result in crop failure. This condition can cause losses for mustard greens farmers in running their businesses. This research proposes an information system that represents the expertise of hydroponic mustard greens farmers in diagnosing pests and diseases in mustard plants as well as solutions to overcome them. This is to make it easier for novice growers and anyone interested in learning about diseases or pests that impact hydroponic mustard greens. The expert system developed is web-based and functions as a user consultation medium in relation to mustard pests and diseases using the forward chaining and certainy factor method to explain the decision tree procedure for mustard plant disease symptoms. With this expert system, farmers do not need to look for people who can explain the problems they face. We found that there were 10 types of pests and diseases and 29 symptoms in the hydroponic mustard plants reviewed in this research.
DOI
10.1109/ICSINTESA62455.2024.10747915
Access Rights
subscription content
Comments
Baihaqi, M. B., Widodo, A. P., & Jie, F. (2024, July). Use of an expert system to diagnose and provide solutions for pests and diseases in hydroponic mustard plants using certainty factor and forward chaining methods. In 2024 4th International Conference of Science and Information Technology in Smart Administration (ICSINTESA) (pp. 523-527). IEEE. https://doi.org/10.1109/ICSINTESA62455.2024.10747915