A Comparative Study of The Weighted High Order Fuzzy Time Series and ARIMA Method in Forecasting Tourist Visits

Abstract

The tourism sector is a strategic sector that plays a crucial role in driving regional economic growth. Tourism is a leading sector in West Nusa Tenggara Province, contributing significantly to regional income, job creation, and community welfare. The presence of leading tourist destinations such as the Mandalika Special Economic Zone, Mount Rinjani, and Gili makes West Nusa Tenggara one of the leading tourist destinations in Indonesia. Local governments, tourism businesses, and other relevant parties need information on future tourist visits to plan the provision of facilities and infrastructure, manage tourist destinations, promote tourism, and develop human resources. This study aims to forecast tourist visits to West Nusa Tenggara. The methods used in this study are the weighted high-order fuzzy time series (WHOFTS) and Autoregressive Integrated Moving Average (ARIMA) methods, and these two forecasting methods are compared. The results of this study showed that WHOFTS performs better than ARIMA, as indicated by the lower MAPE value (WHOFTS is 6.17% and ARIMA is 14.67%). The forecasting results will be useful for stakeholders, especially the government, in formulating policies. The WHOFTS method used in this study cannot be applied to data with long-term seasonal patterns. Suggestion that can be given to future researchers is develop the WHOFTS that can capture additional long-term seasonal patterns