Predictive Analysis of the Amount of Batik Production Using the Fuzzy Sugeno Algorithm
Abstract
To meet market demand, a company must be able to plan and determine the amount of appropriate and timely production to compete with other companies. To support this, we need a system that can determine the product's production amount so that the product can be sold according to expectations and the desired target. This study aims to determine the amount of production through a decision support system using the Fuzzy Sugeno algorithm in the form of logic used to produce a single decision or crisp. This research was conducted on batik production in a company. The problem in the batik production process is the amount of production that differs from the market demand. The factors that influence the process of determining the amount of production are the number of inventories and the number of requests used as variables in this study. The results of this study are in the form of a decision support system that can determine the amount of batik production based on the analysis of the number of requests and the amount of supply used to assist companies in making decisions with a truth value of 80%. Thus, the company can be assisted in determining the amount of production to meet market demand and increase profits and achievement targets by minimizing stockpiling.
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