Expert System to Diagnose Kidney Failure with Web-Based Naïve Bayes Method Expert System to Diagnose Kidney Failure with Web-Based Naïve Bayes Method
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Abstract
Expert system is a development of AI that is designed to meet and facilitate decision making. Although the expert system is artificial intelligence, the expert system has only one domain in problem solving, such as medicine, engineering, and business. The method used in this study is the naïve bayes method. Naïve Bayes is a calculation method with probabilities and statistics in calculations. This research was made by combining information technology knowledge with health science which is intended to facilitate the use of computers in anticipating kidney failure. Kidney failure is a disease that is often experienced by people, especially in Indonesia. Because kidney failure is a deadly disease even though it is often underestimated by the community, especially Indonesia. The purpose of this paper is to assist the public in anticipating kidney failure that is still lacking knowledge and sensitivity to the disease. The application of the expert system is made with the naïve bayes method which has the function to calculate the percentage of presentations due to kidney failure and can help the role of doctors in making decisions in determine the type of kidney failure. In this application, an expert system for diagnosing kidney failure has an accuracy value of 81.67% from 60 test data.
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