Ansari Saleh Ahmar^1,2,*, Eva Boj del Val³, M. A. El Safty⁴, Samirah AlZahrani⁴, Hamed El-Khawaga^5,6

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6007-6022, 2022, DOI:10.32604/cmc.2022.021382 - 11 October 2021

Abstract This study focuses on the novel forecasting method (SutteARIMA) and its application in predicting Infant Mortality Rate data in Indonesia. It undertakes a comparison of the most popular and widely used four forecasting methods: ARIMA, Neural Networks Time Series (NNAR), Holt-Winters, and SutteARIMA. The data used were obtained from the website of the World Bank. The data consisted of the annual infant mortality rate (per 1000 live births) from 1991 to 2019. To determine a suitable and best method for predicting Infant Mortality rate, the forecasting results of these four methods were compared based on More >

Ansari Saleh Ahmar¹, Pawan Kumar Singh², Nguyen Van Thanh^3,*, Nguyen Viet Tinh³, Vo Minh Hieu³

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 523-534, 2022, DOI:10.32604/cmc.2022.017068 - 07 September 2021

Abstract The novel coronavirus has played a disastrous role in many countries worldwide. The outbreak became a major epidemic, engulfing the entire world in lockdown and it is now speculated that its economic impact might be worse than economic deceleration and decline. This paper identifies two different models to capture the trend of closing stock prices in Brazil (BVSP), Russia (IMOEX.ME), India (BSESN), and China (SSE), i.e., (BRIC) countries. We predict the stock prices for three daily time periods, so appropriate preparations can be undertaken to solve these issues. First, we compared the ARIMA, SutteARIMA and… More >