Application of Case Base Reasoning Algorithm in Detecting Disease in Pineapple Fruit
Abstract
Pineapple fruit is a type of horticultural plant that has the potential to be developed. In the process of pineapple cultivation, it is very susceptible to pests and diseases. Diseases that often attack pineapples such as; wilt disease, stem base rot, fusariosis, bacterial rot, and urethral disease. The process of identifying pineapple diseases is often done manually so it takes a long time. In addition, in the process of controlling pests and diseases, farmers only spray pesticides or other handling techniques that are not suitable for the pests and diseases that attack them. Thus, the treatment is not optimal and has an impact on the emergence of new pests and diseases in pineapple. Currently, computer technology can be used in various branches of science, one of which is artificial intelligence. The expert system is a scientific branch of artificial intelligence that can solve problems. The purpose of this research is to assist farmers in identifying pests and diseases in pineapples so that the control process can be carried out optimally, quickly, and on target. The implementation of an expert system uses the Case Base Reasoning (CBR) method which will produce a diagnostic similarity value and provide recommendations for diseases that attack. This research processes data in the form of symptoms seen in pineapple plants. The test results obtained a percentage of 100%. Thus, the application of the CBR method is very relevant in identifying pests and diseases of pineapple plants.
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References
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