In order to model uncertainty in data, the fuzzy intuitionistic alpha-cut modeling interpolation rational Bezier curve process will be examined in this paper. In defining the uncertainty data and then modeling it using a chosen curve function, the basic theories and definitions that will be used are fuzzy set theory, fuzzy intuitionistic, and curve functions under geometrical modeling. This study has three main processes, the first of which is the definition of the uncertainty data using the fuzzy number concept. The fuzzy intuitionistic definition will then be used to calculate the alpha value (also known as the alpha-cut) for both membership values and non-membership values. Following the definition of fuzzy intuitionistic into an alpha-cut value, the fuzzification process will be applied to the data set. Defuzzification will be used after the fuzzification process to produce single values data that are defined as crisp fuzzy data for modeling. Rational Bezier interpolation will be used for visualization of the modeling data for each process in order to make analyses and conclusions.

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