Mobile Expert System to Diagnose Diseases and Pests in Tobacco Using Analytical Hierarchy Process (AHP)

Tobacco, also known as the money tree by the Madurese people, is a second crop after the most cultivated corn. In the process of cultivating tobacco crops, diseases and pests become a threat to the farmers to realize the desire to make a lot of money. Generally, farmers often struggle to distinguish...

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Bibliographic Details
Published in:Journal of physics. Conference series 2020-03, Vol.1477 (2), p.22024
Main Authors: Syarief, Mohammad, Imamah
Format: Article
Language:English
Subjects:
Accuracy
AHP
Analytic hierarchy process
Consistency tests
Diagnosis
Diseases
Expert System
Expert systems
Hierarchies
Insecticides
Pest
Pests
Physics
Signs and symptoms
Symptoms
Tobacco
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Summary:Tobacco, also known as the money tree by the Madurese people, is a second crop after the most cultivated corn. In the process of cultivating tobacco crops, diseases and pests become a threat to the farmers to realize the desire to make a lot of money. Generally, farmers often struggle to distinguish between pests and diseases. This failure will have a significant impact on the treatment, the disease that should be washed with the drug, but because the wrong diagnosis can be solved using insecticide (pest). This research aims to facilitate farmers to obtain information, appropriately diagnose and solutions in overcoming diseases and pests in tobacco. The experts who contributed to this study are agricultural experts in the district office of Sumenep. The method used is Analytical Hierarchy Process (AHP). This method is selected because it can perform consistency tests on data, so it is expected to improve the accuracy of the diagnosis. Based on research that has been done, using 21 data symptoms of diseases and pests, as well as nine types of diseases in tobacco, obtained the accuracy value of the mobile expert system by 65%. This accuracy is achieved by comparing the diagnose results by agricultural experts with the diagnose results using the mobile expert system.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/1477/2/022024