Neural Network Enhancement Forecast of Dengue Fever Outbreaks in Coastal Region

Abstract

Dengue Fever is among the world's fastest-spreading mosquito-borne illnesses. In Indonesia, more than 33 percent of the world community is in danger. The Coastal Zone is one of the region most at risk of contracting dengue fever, particularly from the social and environmental sectors, so an early diagnostic study must deal with this efficiently and effectively. This research aimed to predict and identify the coastal areas with the most severe dengue fever potential to avoid dengue fever. The methodology used is a neural network-based sensitivity Analysis and multiple linear regression. Bagan Deli, Sibolga, Tapanuli Tengah, Langkat, Medan are samples of the coastal regions used in this study. The reports used was secondary data for dengue fever patients suffering and meteorological parameters, the model used in [5-5-1] for prediction, for five years from 2014-2019. The results showed which Langkat (0.4936), Serdang Bedagai (0.4695), The Middle Of Tapanuli (0.4399), Medan (0.4313), and Sibolga (0.3133) are perhaps the most prevalent areas affected by dengue fever with a value of 89.8 percent. The Result is temperature and humidity are the conditions that most affect the transmission of dengue fever.