Comparison of the trend moment and double moving average methods for forecasting the number of dengue hemorrhagic fever patients

Abstract

Spread of dengue hemorrhagic fever (DHF) is influenced by an increase in air temperature due to changes in weather and population density so that there is a lot of exchange of dengue virus through the bite of the Aedes aegypti mosquito. Forecasting models are needed to predict the number of DHF patients in the future so that monitoring of the number of DHF patients can be carried out as anticipation and consideration of decision making. Forecasting the number of patients is based on actual data within 2 (two) previous years by comparing the two methods, namely trend moment and double moving average. To measure the accuracy of the forecasting results from the two forecasting methods, tracking signal and moving range are used. based on the test results, it shows that the forecasting results are said to be good because no one has passed the upper control limit and lower control limit values so that the difference between the actual data and the forecasting results is not too significant and the trend moment more recommended because the difference in actual data and forecasting results are approached and shown in the pattern graph by looking at the data difference in each period.