Dengue Haemorrhagic Fever Outbreak Prediction using Elman Levenberg Neural Network and Genetic Algorithm

Abstract

Dengue Hemorrhagic Fever (DHF) is a very dangerous disease and has threatened human survival. This disease usually spreads easily and causes of death in children especially those younger than 15 years. The purpose of this research is to develop a system that can be used to predict the number of DHF cases in the city of Kupang, Indonesia accurately using improved Elman Levenberg-Marquardt Neural Network algorithm. This study used four (4) input variables, which are the factors that contribute to the spread of DHF, namely: (i) The average temperature, (ii) The average of rainfall, (iii) The humidity and (iv) The sea level. Based on test results, the model can predict DHF cases with RMSE of 1,384.