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Periodicity analysis of tourist arrivals to Banda Aceh using smoothing SARIMA approach

机译:使用平滑Sarima方法的旅游到达Banda Aceh的周期性分析

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Forecasting the number of tourist arrivals who enters a region is needed for tourism businesses, economic and industrial policies, so that the statistical modeling needs to be conducted. Banda Aceh is the capital of Aceh province more economic activity is driven by the services sector, one of which is the tourism sector. Therefore, the prediction of the number of tourist arrivals is needed to develop further policies. The identification results indicate that the data arrival of foreign tourists to Banda Aceh to contain the trend and seasonal nature. Allegedly, the number of arrivals is influenced by external factors, such as economics, politics, and the holiday season caused the structural break in the data. Trend patterns are detected by using polynomial regression with quadratic and cubic approaches, while seasonal is detected by a periodic regression polynomial with quadratic and cubic approach. To model the data that has seasonal effects, one of the statistical methods that can be used is SARIMA (Seasonal Autoregressive Integrated Moving Average). The results showed that the smoothing, a method to detect the trend pattern is cubic polynomial regression approach, with the modified model and the multiplicative periodicity of 12 months. The AIC value obtained was 70.52. While the method for detecting the seasonal pattern is a periodic regression polynomial cubic approach, with the modified model and the multiplicative periodicity of 12 months. The AIC value obtained was 73.37. Furthermore, the best model to predict the number of foreign tourist arrivals to Banda Aceh in 2017 to 2018 is SARIMA (0,1,1)(1,1,0) with MAPE is 26%.
机译:预测旅游商业,经济和工业政策需要进入地区的旅游到货人数,以便需要进行统计建模。 Banda Aceh是Aceh Province的首府,经济活动受到服务业的推动,其中之一是旅游部门。因此,需要预测旅游到达数量来发展进一步的政策。鉴定结果表明,外国游客到班达·亚历族的数据到达遏制趋势和季节性。据称,抵达的人数受到外部因素的影响,例如经济学,政治,假日季节导致数据中的结构休息。通过使用二次和立方方法使用多项式回归来检测趋势模式,同时通过具有二次和立方方法的周期性回归多项式来检测季节性。为了模拟具有季节性效果的数据,可以使用的统计方法之一是Sarima(季节性自回归综合移动平均线)。结果表明,平滑,检测趋势模式的方法是立方多项式回归方法,具有修改的模型和12个月的乘法周期。获得的AIC值为70.52。虽然检测季节性模式的方法是周期性回归多项式立方方法,具有修改模型和12个月的乘法周期。获得的AIC值为73.37。此外,预测外国旅游人数到2017年至2018年的外国旅游人数的最佳模型是Sarima(0,1,1)(1,1,0),Mape是26%。

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