Comparison of Chen and Stevenson–Porter Fuzzy Time Series Methods in Forecasting Room Occupancy Rates of Star-Rated Hotels in Bengkulu Province
DOI:
https://doi.org/10.54065/likelihood.559Keywords:
Room Occupancy Rate, Fuzzy Time Series Chen, Fuzzy Time Series Stevenson-PorterAbstract
Considering the importance of room occupancy rate data to determine the condition of the hotel sector in the future, the most up-to-date data is needed. However, indicators for room occupancy rates for the current month issued by BPS are released in the following month, so there are obstacles in being able to estimate the condition of the hotel sector. There are several methods that can be used to forecast time series data, such as Exponential Smoothing, ARIMA, Moving Average and Fuzzy Time Series. However, in this research, the method that will be used is the Fuzzy Time Series model Chen and Stevenson-Porter. Using Fuzzy Time Series Chen method, the MAPE value was 21.82%, so it can be said that the forecasting ability is quite good. Meanwhile, using the Fuzzy Time Series Stevenson-Porter method, a MAPE value of 11.41% was obtained, so it can be said that the forecasting ability is good. So the better method to use is the Fuzzy Time Series Stevenson-Porter because it produces the smallest MAPE value.
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