Comparison of Naïve Bayes and Certainty Factor Method for Corn Disease Expert System: Case in Bangkalan, Indonesia
Journal Title: International Journal of engineering Research and Applications - Year 2017, Vol 7, Issue 11
Abstract
One of the application of expert system is in agriculture. In this study the expert system is applied to detect the disease in corn plants. Symptoms that indicate a particular disease, serve as a knowledge base on the system. The symptoms used are 46 which can indicate one of 15 types of diseases in corn plants. There are two methods used to classify the diseases of Naïve Bayes and Certainty Factor. The Naïve Bayes method is a simple classfier type that applies Bayes theorems with strong (naïve) independent assumptions. While Certainty Factor is a Classifier method that has a variation in the level of confidence or weight on each of the symptoms entered. Based on the test results, the system using the Certainty Factor method has a better percentage of truth than using the Naïve Bayes method. Experiment result shows the accuracy of up to 80%.
Authors and Affiliations
Mohammad Syarief, Novi Prastiti, Wahyudi Setiawan
Keywords
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- EP ID EP392804
- DOI 10.9790/9622-0711023034.
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