Open AccessIndonesian Tourism Demand Forecasting using Time Series Approach to Support Decision Making Process
Author(s) -
Putu Bella Ayastri Friscintia
Publication year - 2019
Publication title -
kinerja
Language(s) - English
Resource type - Journals
eISSN - 2549-1709
pISSN - 0853-6627
DOI - 10.24002/kinerja.v23i2.1970
Subject(s) - autoregressive integrated moving average , tourism , indonesian , demand forecasting , order (exchange) , time series , process (computing) , foreign exchange , resource (disambiguation) , business , operations research , baseline (sea) , marketing , computer science , economics , finance , engineering , geography , political science , computer network , linguistics , philosophy , archaeology , machine learning , law , monetary economics , operating system
Tourism industry is always growing dan uphold an important role in national economy as the second largest portion of foreign exchange contributor, as well as its role in national employment. In improving tourism industry, forecasting is needed to anticipate the perishable nature of tourism. Therefore, an accurate forecasting is needed as the baseline of strategic resource planning in order to maximize the utilization dan efficiency of the available resources. The objective of this research is to build an accurate model that is able to forecast Indonesian tourism demand. This research use ARIMA algorithm to forecast the arrivals of tourist. The result of this paper is a time-series model for tourist arrivals in Indonesia Keywords: Tourism, Demand Forecasting, ARIMA, Indonesia.