Forward chaining and fuzzy logic tsukamoto methods for decision

Abstract

Abstract Sales recognition at PT. X is important. This will determine the monthly business growth rate. The main factor determining sales recognition is the delivery of goods on time in the current month. In this regard, a well process of allocating goods is needed. This study focuses on goods allocation recommendations to maximize sales recognition. The expert system was built using forward chaining and fuzzy logic Tsukamoto methods. The main principles of Supply Chain Management are also added to the algorithm in order to achieve maximum recommendation results. The end result is “High” and “Standard” recommendations for the allocation of goods based on available data. Recommendation “High” is worth ∼ 3.9M or the equivalent of ∼ 10.4% of the total potential available. However, the real actions taken are still based on decisions from related parties.