International Journal of Soft Computing And Artificial Intelligence (IJSCAI)
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Volume-7,Issue-2  ( Nov, 2019 )
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  Journal Paper

Paper Title
Production Optimization Using Fuzzy Inference System Tsukamoto

Abstract
This paper discusses the application of Fuzzy Inference System Tsukamoto for decision making in production planning at crude palm oil (CPO) company. In this study, the optimal amount of CPO production in year 2014 are available. The objective is to help the production manager’s for determine the optimal number of CPO production, so that can be effective and efficient in production planning. Data demand, inventory and production in 2014 as the input for FIS Tsukamoto to determine the optimal number of productions. There are three steps of FIS Tsukamoto to generate the inputs. Firstly is the Fuzzification, in this step the data input that call crisp set are transformed to the fuzzy set using the fuzzy theory. Secondly is the Inference, in this step all the fuzzy set must be sent to knowledge base that contains n fuzzy rule in the form of IF-THEN. Fire strength (antecedent membership values or α) will be sought at each rule. If more than one rule, it will be an aggregation of all the rules there are nine rules used in this study. Lastly is the defuzzification, the results of the second step above which still in fuzzy sets, then recovered into the crisp sets as an output by using the Center of Gravity Method. In conclusion, the result of the calculation shows that the FIS Tsukamoto can be optimized in terms of the amount of production and profits at Palm Oil Mill Company. Keywords- Fuzzy Logic, Decision Making, Production Planning, Fuzzy Inference System Tsukamoto


Author - Abdul Talib Bon, Silvia Firda Utami

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