Open AccessMeasurement of Similarity and Design Interface for Soybean Disease Diagnosis
Author(s) -
Adriana Sari Aryani,
Dian Kartika Utami
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.b1034.0782s719
Subject(s) - blight , similarity (geometry) , point of delivery , downy mildew , mathematics , horticulture , biology , computer science , artificial intelligence , image (mathematics)
The similarity of the target case is determined by measuring how close each attribute of the target is similar to the stored case in the case base. Similarities are usually normalized to fall within a range of 0 to 1. The soybean is one of the most important bean in the world, providing vegetable protein for millions of people and ingredients for hundreds of chemical products. Several diseases, including root and stem rot, pod and stem blight, frogeye leaf spot, brown spot, downy mildew, leaf blight and purple seed stain, and stem rot (white mold). In a case-based reasoning system for the identification of diseases of soybean plants provide solutions recommended by experts in diseases of soybean in accordance with a similar case or a similar matches within the database storage plant disease cases. Similarity value where 0 is totally dissimilar and 1 is an exact match. if similarity value equal zero then system will keep a set of data will be save temporary and need validation as a new case from the expert. The system give a recommended solution from similarity formula with the threshold which given by the expert.