Strengthening economy through tourism sector by tourist arrival prediction

Indonesian Operations Research Association - International Conference on Operations Research 2017

Supriatna, A.^1 ; Subartini, B.^1 ; Hertini, E.^1 ; Sukono^1 ; Rumaisha^1 ; Istiqamah, N.^1

Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Indonesia^1

关键词: Indonesia;    National economy;    National governments;    Seasonal autoregressive integrated moving averages;    Time series method;    Time-periods;    Tourism sectors;    Tourist attractions;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/332/1/012005/pdf
DOI  :  10.1088/1757-899X/332/1/012005

来源: IOP

【 摘 要 】

Tourism sector has a tendency to be proposed as a support for national economy to many countries with various of natural resources, such as Indonesia. The number of tourist is very related with the success rate of a tourist attraction, since it is also related with planning and strategy. Hence, it is important to predict the climate of tourism in Indonesia, especially the number of domestic or international tourist in the future. This study uses Seasonal Autoregressive Integrated Moving Average (SARIMA) time series method to predict the number of tourist arrival to tourism strategic areas in Nusa Tenggara Barat. The prediction was done using the international and domestic tourist arrival to Nusa Tenggara Barat data from January 2008 to June 2016. The established SARIMA method was (0,1,1)(0,0,2)12with MAPE error of 15.76. The prediction for the next six time periods showed that the highest number of tourist arrival is during September 2016 with 330,516 tourist arrivals. Prediction of tourist arrival hopefully might be used as reference for local and national government to make policies to strengthen national economy for a long period of time.