PREDICTION THE NUMBER OF PATIENTS AT DENGUE HEMORRHAGIC FEVER CASES USING ADAPTIVE NEURAL FUZZY INFERENCE SYSTEM (ANFIS)
Journal Title: International Journal of Innovative Research in Advanced Engineering - Year 2017, Vol 0, Issue 0
Abstract
Dengue Hemorrhagic Fever is one of the dangerous infectious diseases that can cause death within a short time and often cause epidemic. The spread of dengue fever outbreaks globally with frequency levels tend to be higher during the period of last 50 years gave rise to an idea that systematic prevention. The purpose of this paper was to design an application to predict the number of dengue hemorrhagic fever patients with ANFIS method. Weather factors such as air humidity, air temperature, rainfall and number of rain days is used as the factors that influence the incidence of dengue hemorrhagic fever. In this paper using three methods for establishment of FIS: Grid Partition, Substractive Clustering and Fuzzy C Means. By simulating three methods for maximum predicted results, it was found that the ANFIS method with Grid Partition as the establishment of FIS is the best model to generate value with the smallest RMSE testing is 0.71. It indicates That ANFIS models is well proven to be used in predicting The cases of dengue fever
Authors and Affiliations
Basuki Rachmat, Oky Dwi Nurhayati, Suryono Suryono
Keywords
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- EP ID EP177303
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