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All Journal Journal of Research in Mathematics Trends and Technology
Manik, Vepita Vemka
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Decision Sciences, Operations Research & Management Mathematics

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Comparison of Tsukamoto and Mamdani Methods for Forecasting Rice Production in North Sumatra for 2024 Dewi, Enita; Nababan, Meni Nurmasita; Manik, Vepita Vemka; Panggabean, Theresia Defi Lasmaria
Journal of Research in Mathematics Trends and Technology Vol. 5 No. 2 (2023): Journal of Research in Mathematics Trends and Technology (JoRMTT)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jormtt.v5i2.16900

Abstract

The application of the Tsukamoto and Mamdani methods is widely used in predicting an object based on the objective function to be achieved. This study compares both methods for determining rice production to identify the best method for prediction processes based on error values or forecasting accuracy levels. In predicting rice production, fuzzification and defuzzification stages occur. Actual data that is vague is processed into crisp numbers. Based on the calculation of error values or forecasting accuracy results for each method, the Mean Absolute Percentage Error (MAPE) value for the Mamdani method is 30% and the Tsukamoto method is 22%. Therefore, the forecasting system using the Tsukamoto method is sufficiently effective to predict production results
Co-Authors Enita Dewi Nababan, Meni Nurmasita Panggabean, Theresia Defi Lasmaria