Implementation of Forward Chaining in a Web-Based Fruit Plant Disease Diagnosis Expert System

Abstract

Horticultural plants are classified into several types, one of which is dicotyledon fruit plants, dicotyledonous fruit plants are two-piece plants with seeds having two institutional leaves or cotyledons, dicotyledonous fruit plants have many benefits from their stems, leaves and fruit, but there are problems when farmers or people plant the plants. dicot fruit, that is, there is a disease that attacks the plant. Because the types of diseases that attack fruit plants are quite diverse but have almost the same symptoms, farmers and the public are still confused and do not have a definite scientific basis for knowing the types of diseases and the correct treatment method. Farmers and the community still rely only on experience from problems that exist around them and do not come from the knowledge of an expert who has mastered the field. So an expert system for dicotyledon plant diseases is needed. This expert system adopts knowledge from plant experts and is built using the Forward Chaining method which can predict disease based on the criteria and symptoms that appear to reach conclusions. This expert system produces accurate data based on an expert's knowledge which is poured into a computer program which will later be used to diagnose plant diseases and provide solutions to the disease.