Abstract
Tourists get attracted towards Malaysia because of our culture and geography. Apart from heritage and culture, the tourists from all over the world visit here for various purpose. Therefore, forecasting tourist arrivals with high level of accuracy becomes important because it can ensure the development of tourism industries. So, this study focuses on tourist arrivals to Malaysia. This paper attempts to define the component of patterns exist in the time series data, to determine the most suitable model best fits in data series by using the error measure that are Mean Square Error (MSE) and Mean Absolute Deviation (MAD) and to forecast the one-step ahead forecast on the best model. In this study, data of tourist arrivals to Malaysia has been obtained from January 2000 until December 2018. All 228 monthly data were analyzed by using selected Univariate Modeling. The result found that tourist arrivals to Malaysia has a linear trend model and Double Exponential Smoothing with α = 0.17 was the best model for this time series.
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