FORECASTING TOURISM MARKET DEMAND IN HUNAN PROVINCE USING ARIMA MODEL - Quan Qin (Delta: Jurnal Ilmiah Pendidikan Matematika, 2021)
Hunan Province is a province with large tourism resources, and it’s tourism occupies a significant position in economic development. In recent years, Hunan province is in a critical period of transition from a major tourist province to a staggering tourist province. Therefore it is of great significance to analyze and predict the development trend of the future tourism market demand in Hunan Province and provide the government and tourism enterprise managers with the scientific market decision. Based on time-series analysis and forecasting theory, this paper attempts to use the time-series data of the number of domestic tourists in Hunan Province which from 2000 to 2019 and construct model autoregressive and integrated moving average (ARIMA) to predict the number of tourists in the Hunan Province in the next four years. The results show that the error between the predicted value and the true value is small. Therefore, the prediction effect of the model is well, which will provide a theoretical basis for the government to establish relevant policies. However, considering the characteristics of time-series data, the model needs to be further revised and even effectively combined with other models to gain better forecasting results.