<![CDATA[The purpose of this study is to create a system that can predict the need for vitamin A in a certain period, and provide convenience to related parties to meet the needs of the vitamin. Vitamin A is the most essential nutrient, this is because food consumption is not sufficient and is still low so it must be met from the outside. In this study, the method used to predict the need for vitamin A is the fuzzy mamdani method with input variables namely stock and demand and output variables namely needs. The predictions made are based on past statistics and on the basis of the characteristics of past vitamin A consumption. To calculate the error in predicting using the mean absolute percentage error (MAPE). Analysis of system requirements built using an object approach with Unified Modeling Language (UML) tools. The results of the overall prediction obtained the highest average accuracy value of 97.93% with an average error value as small as 2.07% while the lowest average accuracy value was 92.57% with an average error value as small as 7.43%. Testing on the system obtained a 100% functional value that went well in accordance with the needs analysis that had been made, so that the system had provided predictive information on vitamin A needs for a certain period and provided convenience for related parties to fulfill these needs.]]>
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