Based on data presented by the National Strategic Food Price Information Center on Monday (6/5/2019), all food commodity prices rose. Wear prices affect people's purchasing power and the main raw materials in the area. To overcome this problem, it is necessary to think that to create a site-based application that can monitor food prices and can predict food price increases, predictions are expected to be a purchasing decision support system to control prices. The methodology used in this application is V Model, the programming language used is PHP using the Laravel 5.8 framework to develop the application. This application uses the Fuzzy Time Series method, which is to forecast or predict the price of commodity types. Is to provide information related to commodity prices in the market, also predict the price of commodity types for the months ahead, this is intended to take action to compile a sudden increase in price. From the test results the estimated price uses the average absolute error percentage (MAPE). And the prediction results obtained with a MAPE value of -0.013%.
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