The analysis performance method naive bayes andssvm determine pattern groups of disease

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Abstract

Information is a very important element and into the daily needs of the moment, to get a precise and accurate information is not easy, this research can help decision makers and make a comparison. Researchers perform data mining techniques to analyze the performance of methods and algorithms naï ve Bayes methods Smooth Support Vector Machine (ssvm) in the grouping of the disease.The pattern of disease that is often suffered by people in the group can be in the detection area of the collection of information contained in the medical record. Medical records have infromasi disease by patients in coded according to standard WHO. Processing of medical record data to find patterns of this group of diseases that often occur in this community take the attribute address, sex, type of disease, and age. Determining the next analysis is grouping of four ersebut attribute. From the results of research conducted on the dataset fever diabete mellitus, naï ve Bayes method produces an average value of 99% and an accuracy and SSVM method produces an average value of 93% accuracy.

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Sitanggang, R., Tulus, T., & Situmorang, Z. (2017). The analysis performance method naive bayes andssvm determine pattern groups of disease. In Journal of Physics: Conference Series (Vol. 930). Institute of Physics Publishing. https://doi.org/10.1088/1742-6596/930/1/012031

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