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Articles
Published: 31-03-2022

Comparative analysis of Tsukamoto and Sugeno fuzzy algorithms to determine the amount of batik production based on supply data and the number of requests

Universitas Amikom Yogyakarta
predictions tsukamoto sugeno forecasting

Abstract

Batik Jiwo Creation is a batik convection and sales shop that stands in the city of Sukoharjo. The amount of demand that changes every period causes uncertainty in determining the company's production amount in the coming period. Planning the number of products is very important in meeting market demand correctly and in the right amount. Analysis of determining the amount of production is carried out using the Fuzzy Tsukamoto and Sugeno Algorithm based on the amount of inventory and the number of requests. Tsukamoto and Sugeno algorithm is a method of fuzzy inference system. In the Tsukamoto method, every consequence of the if-then rule must be represented by a fuzzy set with a monotonous membership function, while the Sugeno method has the final form in the form of constants or linear equations. Based on the MAD error value on Fuzzy Tsukamoto is 17.93 while on Fuzzy Sugeno it is 210.73. This shows that the Fuzzy Tsukamoto method is better used in the calculation of production forecasting. This comparison algorithm is used to help determine the amount of production in the next period depending on the amount of demand and supply from the previous period.

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How to Cite

Kusumastuti, Rajnaparmaitha. 2022. “Comparative Analysis of Tsukamoto and Sugeno Fuzzy Algorithms to Determine the Amount of Batik Production Based on Supply Data and the Number of Requests”. JNANALOKA 3 (1):11-16. https://doi.org/10.36802/jnanaloka.2022.v3-no1-11-16.