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

The spread of Dengue Hemorrhagic Fever (DHF) is influenced by an increase in air temperature due to changes in weather, humidity and rainfall. Another factor that also affects the population density is the large 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 can be done to increase or decrease the number of DHF patients in anticipation, consideration and decision making. Forecasting the number of patients is based on actual data within 2 (two) previous years, namely 2016 to 2017 by comparing the two forecasting methods, the Trend Moment and Double Moving Average methods. Comparison of forecasting results performed is on actual data and forecast results in 2018 as trial data. The forecasting accuracy method is used the Tracking Signal and Moving Range methods to measure the accuracy of forecasting results from the two forecasting methods used. Based on the trials conducted, the forecasting results presented show that the forecasting results are said to be good because no one has passed the Upper Control Limit (UCL) and Lower Control Limit (LCL) values ​​so that the difference between the actual data and the forecasting results is not too significant and the use of the Trend Moment method more recommended because the difference in actual data and forecasting results are close to and shown in the pattern graph by looking at the difference in data in each period.

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