Forecasting Shallot Prices in West Sumatra Province Using the Fuzzy Time Series Method of the Singh Model and the Cheng Model

Huriati Khaira, F. Fitri, N. Amalita, D. Permana
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Abstract

Shallots are one of the leading spices that are widely used by humans as food seasoning and traditional medicine. The price of shallots always fluctuates which can affect the buying and selling of consumers and producers. Therefore, forecasting is used as a reference to be able to predict the price of shallots in the future and can provide convenience to the public for the condition of shallot prices in the next period. The forecasting method used is the fuzzy time series (FTS) method. FTS is a method whose forecasting uses data in the form of fuzzy sets sourced from real numbers to the universe set on actual data. Forecasting models used in this study are Singh's FTS model and Cheng's model. The data used is monthly data on shallot prices in West Sumatra Province for the period January 2018 to March 2022. The results obtained in this forecast are the Singh model FTS has a smaller MAPE value of 4.41% with a forecasting accuracy value of 95.59 %. This means that Singh's FTS model is better at predicting the price of shallots in West Sumatra Province.
利用Singh模型和Cheng模型的模糊时间序列方法预测西苏门答腊省大葱价格
青葱是一种重要的香料,被人类广泛用作食品调味料和传统医药。青葱价格的波动会影响消费者和生产者的买卖。因此,预测作为一种参考,可以预测未来葱的价格,为公众了解下一时期的葱价格状况提供方便。所采用的预测方法是模糊时间序列(FTS)方法。FTS是一种利用来自实数的模糊集形式的数据到实际数据的宇宙集进行预测的方法。本研究使用的预测模型是Singh的FTS模型和Cheng的模型。使用的数据是2018年1月至2022年3月期间西苏门答腊省葱价格的月度数据。预测结果表明,Singh模型FTS的MAPE值较小,为4.41%,预测精度为95.59%。这意味着辛格的FTS模型在预测西苏门答腊省青葱价格方面效果更好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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