Issue |
E3S Web Conf.
Volume 328, 2021
International Conference on Science and Technology (ICST 2021)
|
|
---|---|---|
Article Number | 04009 | |
Number of page(s) | 4 | |
Section | Information System, Big Data, Design Application, IOT | |
DOI | https://doi.org/10.1051/e3sconf/202132804009 | |
Published online | 06 December 2021 |
Implementation Of K-Nearest Neighbor - Certainty Factor For Expert System Detection Of Idiopathic Thrombocytopenic Purpura
Informatics Faculty of Computer Science, Universitas Pembangunan Nasional “Veteran” Jawa Timur, Indonesia.
* Corresponding author : evapuspaningrum.if@upnjatim.ac.id
Idiopathic Thrombocytopenic Purpura (ITP) is an autoimmune disorder. ITP can occur in children and adults. This disease can be fatal because the platelet count is low due to the destruction of excessive platelets so that it can interfere with vital organs and bleeding occurs. The lack of knowledge of ordinary people about ITP disease, so many people assume that bruises and nosebleeds on the body are caused by fatigue. For that, we need a system that can imitate the expertise of an expert in diagnosing this disease based on the symptoms felt. The method used to support the expert system is the K-Nearest Neighbor and Certainty Factor methods which are a combination of 2 methods, where the classification results from the K-Nearest Neighbor method will be given a certainty value by the Certainty Factor method so as to produce a prediction. The results of combining the two methods can produce certainty in the diagnosis. Based on the test results using 3 test scenarios using parameter values k=3, k=5, k=7 and the results obtained the highest accuracy value with parameter value k=7 obtained an accuracy rate of 90,9%.
Key words: Idiopathic Thrombocytopenic Purpura / Expert System / KNN / Certainty Factor
© The Authors, published by EDP Sciences, 2021
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