Analisa Perbandingan Algoritma Fuzzy Tsukamoto Dan Sugeno Untuk Menentukan Jumlah Produksi Batik Berdasarkan Data Persediaan Dan Jumlah Permintaan (Studi Kasus : Batik Jiwo Creation, Sukoharjo)

Rajnaparmaitha Kusumastuti

JNANALOKA
Vol. 03 No. 01 Maret Tahun 2022

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.