The Implementation of Fuzzy Time Series in Forecasting The Number of Tourist Visits
DOI:
https://doi.org/10.30812/varian.v8i3.4890Keywords:
Forecasting, Fuzzy Time Series, Time Series, TourismAbstract
The development of tourism in West Nusa Tenggara (NTB) Province is supported by its geographical conditions, including scattered small islands (gilis), a tropical climate, and the cultural peculiarities of the Sasak and Mbojo Tribes, thereby becoming an attraction in the development of global tourist destinations. Tourism development in NTB Province would be more attractive with the establishment of the Mandalika National Tourism Development Strategic Area (KSPPN). This research aims to predict the number of tourist visits. A method to forecast the number of tourist visits in NTB Province is needed to assist the government in preparing appropriate facilities and infrastructure in the event of a possible surge in tourist visits. The method used in this study is the Fuzzy Time Series to predict the number of tourist visits in NTB Province. The data used in this study were secondary data sourced from the NTB government tourism office. The result of this research was that the Fuzzy Time Series method was effective in predicting the number of tourist visits in NTB Province, with an accuracy of 90.29%. The forecast result, generated using the Fuzzy Time Series method, was not significantly different from the actual data; in other words, it was almost identical to the actual data. The forecast for tourist visits to the NTB province in the 48th period remains unchanged until the 53rd period, namely 80,739.7 people. The FTS method used in this study cannot be applied to data with long-term seasonal patterns. A suggestion for future researchers is to develop a classical FTS that captures additional long-term seasonal patterns.
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Copyright (c) 2025 Istin Fitriana Aziza, Siti Soraya, Sahdan, Husain, Ni Putu Nanik Hendayanti, Lisa Harsyiah
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