Naive Bayes Method in Determining Diagnosis of Corn Plant Disease
Abstract
Corn is one of the leading agricultural commodities from the food crop sub-sector that is multi-purpose and has strategic value to be developed. At this time, corn is not only used for food but also for animal feed, and also fuel. The amount of production, productivity, and price of corn always fluctuates due to the influence of the ever-changing amount of demand and supply. The high demand for maize in the domestic market is an opportunity for Indonesia to balance the demand for and supply of maize. An expert system is a system that seeks to adopt human knowledge to computers so that computers can solve problems as is usually done by experts. A good expert system is designed to be able to solve a particular problem by imitating the work of experts. The naive Bayes method is a method used to predict probability. While the Bayes classification is a statistical classification that can predict the class of a probability member. For a simple Bayesian classification known as the Naïve Bayesian Classifier, it can be assumed that the effect of an attribute value of a given class is independent of other attributes. From the results of testing on the Expert System Application that was built, the expert system can solve the problem that it can display the diagnostic results quickly and precisely based on the symptoms entered by the user. Based on the tests carried out with the accuracy of the diagnosis obtained from the comparison between the results of expert diagnoses and system diagnoses with a percentage of 90%, the system can be clarified that it is feasible to use.
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