MATEC Web Conf.
Volume 215, 2018The 2nd International Conference on Technology, Innovation, Society and Science-to-Business (ICTIS 2018)
|Number of page(s)||5|
|Section||Emerging Technologies and Applied Science|
|Published online||16 October 2018|
Comparison of Case-Based Reasoning and Dempster Shafer on Expert System of Cassava Disease Identification
Institut Teknologi Padang, Informatics Engineering Study Program, Padang, Indonesia
* Corresponding author: firstname.lastname@example.org
This study aims to develop a web-based expert system that can identify cassava disease using Case-Based Reasoning Method and Shafer Dempster Method, and to know the performance comparison of both based on the accuracy of identification. Case-Based Reasoning (CBR) is a computer-generated system that uses old knowledge to solve new problems. CBR provides solutions to new cases by looking at the oldest cases that are closest to new cases. The identification process is done by entering new cases containing the symptoms to be identified into the system, then perform the process of calculating the value of similarity between the new case and the base case using the nearest neighbor method. Dempster Shafer based on two ideas is the idea of obtaining degrees of confidence of subjective possibilities and the rule of dempster safer itself to combine degrees of confidence based on the evidence obtained. This expert system is built using PHP programming language and MySQL data base. The output of the system is the percentage of identification result of both methods. Testing and analysis results show that Case-Based Reasoning provides better identification accuracy than Dempster Shafer.
© The Authors, published by EDP Sciences, 2018
This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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