• DocumentCode
    1823127
  • Title

    The performance of GM (1,1) and ARIMA for forecasting of foreign tourists visit to Indonesia

  • Author

    Kharista, Anung ; Permanasari, Adhistya Erna ; Hidayah, Indriana

  • Author_Institution
    Dept. of Electr. Eng. & Inf. Technol., Gadjah Mada Univ., Yogyakarta, Indonesia
  • fYear
    2015
  • fDate
    20-21 May 2015
  • Firstpage
    33
  • Lastpage
    38
  • Abstract
    Forecasting can be used for helping the decision-makers to determine the next business strategy to improve the quality of Indonesia tourism such as the improvement of the accommodation facility like transportation and lodging, public services, and promotion to introduce Indonesia tourism objects. This research compared the forecasting performance between GM (1,1) and ARIMA models to determine the best method to forecast the number of foreign tourists visit to Indonesia by using limited data. The data used is the national data of foreign tourists arrival in the airport entrance obtained from the BPS Indonesia in the period of 2002 to 2014. From the result of the forecasting accuracy based on RMSE and MAPE showed that GM (1,1) is smaller than of the ARIMA. It indicates that the performance of GM (1,1) is better than ARIMA to forecast the number of foreign tourists visit. However, it can be concluded that both of the models are able to forecast properly because both of them produce MAPE less than 10%.
  • Keywords
    data mining; forecasting theory; travel industry; ARIMA model; BPS Indonesia; Grey model; MAPE; RMSE; business strategy; foreign tourist visit forecasting; tourism industry; Accuracy; Autoregressive processes; Biological system modeling; Data models; Forecasting; Mathematical model; Predictive models; ARIMA; GM (1,1); MAPE; RMSE; forecasting; tourists;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Technology and Its Applications (ISITIA), 2015 International Seminar on
  • Conference_Location
    Surabaya
  • Print_ISBN
    978-1-4799-7710-9
  • Type

    conf

  • DOI
    10.1109/ISITIA.2015.7219949
  • Filename
    7219949