Comparison of Tsukamoto and Mamdani Methods for Forecasting Rice Production in North Sumatra for 2024

Authors

  • Enita Dewi Statistics Department, Universitas Sumatera Utara, Indonesia
  • Meni Nurmasita Nababan Mathematics Department Universitas Sumatera Utara
  • Vepita Vemka Manik Mathematics Department Universitas Sumatera Utara
  • Theresia Defi Lasmaria Panggabean Mathematics Department Universitas Sumatera Utara

DOI:

https://doi.org/10.32734/jormtt.v5i2.16900

Keywords:

Defuzzification, Forecast, Fuzzification, Mamdani, Tsukamoto

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

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Published

2023-09-30

How to Cite

[1]
E. . Dewi, M. N. . Nababan, V. V. . Manik, and T. D. L. . Panggabean, “Comparison of Tsukamoto and Mamdani Methods for Forecasting Rice Production in North Sumatra for 2024 ”, J. of Research in Math. Trends and Tech., vol. 5, no. 2, pp. 29-44, Sep. 2023.