Artificial Neural Network for Health Data Forecasting, Case Study: Number of Dengue Hemorrhagic Fever Cases in Malang Regency, Indonesia

Dengue Hemorrhagic Fever (DHF) has become one of the most deadly diseases in the world. Diseases caused by Aedes-type mosquitoes are found in many tropical countries, one of them in Indonesia. Indonesia becomes the country with the highest number of DHF cases in ASEAN, even among the highest in the world. Malang Regency is one of dengue endemic areas in Indonesia. DHF’s current handling strategy is more reactive than anticipatory. As a result, the opportunity to prevent transmission and control the epidemic is reduced. On this basis, efforts should be made to deal with DHF cases. One effort that can be done is to predict the number of dengue cases that will occur in the future. With the forecasting, Malang District Health Office can immediately formulate strategies and take precautions quickly. Also required visualization on the map to show the spread of dengue cases so easy to do the analysis. Artificial Neural Network Method (ANN) is used to predict the number of dengue cases in Malang Regency. The independent variables used as input are the number of dengue cases in each neighboring Puskesmas (Pusat Kesehatan Masyarakat or Community Health Centers) and weather conditions in Malang Regency. After the forecasting, the results obtained are then visualized using the Google Maps API. The Google Maps API provides the ability to display each of the Puskesmas points along with a description of the number of forecasting cases on a Google Maps map through a web browser. This research produced a model that can predict the number of dengue cases in Malang Regency and visualization capable of displaying the spread of cases.