In this study discusses the application of fuzzy logic in solving production problems using the Tsukamoto method and the Sugeno method. The problem that is solved is how to determine the production of woven fabric when using three variables as input data, namely: stock, demand and inventory of production costs.The first step is to solve the problem of woven fabric production using the Tsukamoto method which is to determine the input variables and output variables which are firm sets, the second step is to change the input variable into a fuzzy set with the fuzzification process, then the third step is processing the fuzzy set data with the maximum method. And the last or fourth step is to change the output into a firm set with the defuzzification process with a weighted average method, so that the desired results will be obtained in the output variable. The solution to the production problem using the Sugeno method is almost the same as using the Tsukamoto method, it's just that the system output is not a fuzzy set, but rather a constant or a linear equation. The difference between the Tsukamoto Method and the Sugeno Method is in consequence. The Sugeno method uses constants or mathematical functions of the input variables.From the calculation data of the production of Mlaki Wanarejan Utara Pemalang woven fabric according to Tsukamoto's method in March 2017 using Weka's rule obtained 343 woven fabrics in meters, while using the Sugeno method obtained 371 woven fabrics in meters. While according to Tsukamoto's method in March 2017 using monotonous rules obtained 313 woven fabrics in meters, then using the Sugeno method obtained 321 woven fabrics in meters, while according to the company's production data in March 2017 produced 340 woven fabrics in meters, then from the analysis direct comparison with the original data in the company can be concluded that the method that is closest to the truth value is the production obtained by processing data using the Tsukamoto method using the Weka rules.