Forecasting Rice Price with Double Exponential Smoothing and Fuzzy Time Series Methods (Case Study: Price of Rice in Mataram City)
DOI:
https://doi.org/10.29303/emj.v5i2.123Keywords:
Double Exponential Smoothing Holt, Fuzzy Time Series Cheng, Rice Price , MAPE, MSEAbstract
Rice has become the main staple food for almost the entire population of Indonesia. However, in Indonesia, the price of food commodities (rice) often fluctuates in price. Due to the rapid fluctuation of rice prices and the uncertainty in the future, it is necessary to forecast rice prices. This study aims to predict the price of rice in the city of Mataram using the Holt double exponential smoothing method and the Cheng fuzzy time series. The model's performance is based on Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE) indicators. Forecasting model based on Holt's double exponential smoothing method, the MSE value is 705967.4994 and the MAPE value is 7.91%. On the other hand, based on Cheng's fuzzy time series method, the performance of the forecasting model based on the MSE indicator is 627400.307 and based on the MAPE value of 7.39%. Based on these results, Cheng's fuzzy time series method is more accurate than Holt's double exponential smoothing method.References
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