Aulia, M. Syahdan
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Implementation of Case Based Reasoning and Forward Chaining Algorithm to Diagnose Brocoly Plant Disease Aulia, M. Syahdan; Hasdiana, Hasdiana; Dalimunthe, Yulia Agustina
Al'adzkiya International of Computer Science and Information Technology (AIoCSIT) Journal Vol 2, No 1 (2021)
Publisher : Al'Adzkiya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55311/aiocsit.v2i1.93

Abstract

Doing a broccoli crop farming business is very promising, but there is little knowledge that farmers and the community have about the types of broccoli plant diseases that often attack these plants. By utilizing an expert system, which is able to make a rapid, precise, and accurate diagnosis of the symptoms caused, it is hoped that it will be able to help farmers in anticipating losses caused by disease attacks. Using the Forward Chaining method to determine conclusions starting from a set of facts by looking for rules that match the allegations, and using the Case Based Reasoning method that can solve new case problems by looking for similarity values on a case basis. From the sample cases taken are three symptoms of black rot disease, three symptoms of clubroot, and three symptoms of powdery mildew. Produces a value of 81.81% for black rot, then the system will provide a solution for the disease. Keyword: Broccoli Plant Diseases , Case Based Reasonin, Forward Chaining, Expert System.