The daily needs of the people of Central Aceh cannot be separated from agricultural commodities such as tomatoes, shallots, garlic, and others. Some of these agricultural commodities have sharp price fluctuations, such as tomatoes. When the supply of tomatoes in the market is reduced, the price can be much higher than the normal price. Conversely, when the supply of tomatoes is excessive, the price will fall far below the normal price. This is influenced by various factors such as the harvest season, the amount of production, the amount of public consumption and others. Based on these problems, we need a method to be able to estimate the price of tomatoes so that it can be used to support decision making related to price issues. Forecasting is one of the solutions to be able to estimate the movement of tomato commodity prices. The method used for forecasting tomato prices is High Order Fuzzy Times Series Multifactors. In this method, subinterval formation is carried out using Fuzzy C–means. To calculate the error rate of forecasting results in this study using the Mean Square Error (MSE). Based on the results of the tests carried out, the large values of the training and order data used in forecasting do not guarantee a low error rate.
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