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International Journal of Academic Research in Business and Social Sciences

Open Access Journal

ISSN: 2222-6990

Forecasting Dengue Outbreak Data Using ARIMA Model

Nur Aqilah Ali, Nur Syuhada Muhammat Pazil, Norwaziah Mahmud, Siti Hafawati Jamaluddin

http://dx.doi.org/10.6007/IJARBSS/v11-i6/10106

Open access

Dengue fever is an internationally recognised virus that is spread by mosquitoes and can result in death. From recorded cases, Selangor has the highest rate of dengue infection among Malaysian populations. Corona disease (COVID-19), a new pandemic that has swept the globe, like Selangor, has prompted this report on the pattern of dengue cases during COVID-19 pandemic. Due to the new outbreak of COVID-19, the Movement Control Order (MCO) has been extended from time to time, and with most health resources at the state and federal levels being used to combat COVID-19, dengue control activities have been limited to a non-contact activity in outbreaks and hotspot areas. The importance of this study is to investigate the increase in dengue cases in Selangor because Selangor recorded the highest number of cases in Malaysia. Considering that there are not many studies conducted in Selangor, this study is important to predict dengue cases, and the authorities can take immediate action to overcome this problem. The aim of this research is to find the best ARIMA model for predicting the dengue cases in Selangor in the future. Several ARIMA models were used to test dengue cases data obtained in Selangor in order to achieve the objectives. The best model was calculated by comparing 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 was calculated using the best model generated. The model for which the values of criteria are the smallest is considered as the best model. Hence ARIMA (1,1,2) was found to be the best model for predicting the dengue cases data series and this model is used to predict the number of dengue cases in Selangor with the smallest Mean Square Error (MSE) value of 12837.4327 and Root Mean Square Error (RMSE) value of 113.3024. The forecasted values showed a decreasing number of dengue cases. This study was carried out using R- studio software and excel. Further research can be conducted using another time series method, for example Holt-winters method.

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In-Text Citation: (Pazil et al., 2021)
To Cite this Article: Pazil, N. S. M., Mahmud, N., Jamaluddin, S. H., & Ali, N. A. (2021). Forecasting Dengue Outbreak Data Using ARIMA Model. International Journal of Academic Research in Business and Social Sciences, 11(6), 1746–1755.