Prediction of dengue outbreak: a comparison between ARIMA and Holt-Winter’s methods / Nur Aqilah Ali

Ali, Nur Aqilah (2021) Prediction of dengue outbreak: a comparison between ARIMA and Holt-Winter’s methods / Nur Aqilah Ali. [Research Reports] (Unpublished)


Dengue cases is a globally known infection in which the virus is transmitted by mosquitoes and can lead to death. Selangor has been reported to have the highest incidence of dengue infection among the communities in Malaysia. There is currently a new pandemic, COVID-19, which occurred all over the world, including Selangor, and which led to this study on the pattern of dengue cases during COVID-19. The aim of this study was to develop the best model to predict the future value of dengue cases in Selangor. In order to meet the objectives, the ARIMA method and the Holt’s Winter method are used to evaluate dengue case data collected in Selangor. The best model is chosen by evaluating the Mean Square Error (MSE), Root Mean Square Error (RMSE) and Mean Absolute Percent Error (MAPE) measurement errors. Then, the predicted number of dengue cases is calculated using the best model generated. The best model can be used to predict dengue cases in Selangor is Additive Holt-Winter method since it showed the lowest values of all measurement errors. The trend of dengue in Selangor during COVID-19 showed that fewer cases occurred compared to the phase in which COVID-19 was free. In conclusion, with certain precautions that may be applied by the government to prevent people from going out freely in public places, the number of dengue can be reduced due to factors that can be avoided.


Item Type: Research Reports
Email / ID Num.
Ali, Nur Aqilah
Subjects: Q Science > QA Mathematics > Probabilities
R Medicine > RC Internal Medicine > Chronic diseases > Dengue
Divisions: Universiti Teknologi MARA, Perlis > Arau Campus > Faculty of Computer and Mathematical Sciences
Keywords: Prediction ; Dengue ; Selangor ; ARIMA model ; Holt-Winter’s Model
Date: January 2021
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