Open AccessForward chaining and fuzzy logic tsukamoto methods for decision
Author(s) -
Yusuf Saefudin,
Agung Triayudi,
Ira Diana Sholihati
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1088/1/012018
Subject(s) - chaining , fuzzy logic , forward chaining , order (exchange) , computer science , process (computing) , operations research , scheme (mathematics) , expert system , operations management , business , artificial intelligence , economics , engineering , finance , mathematics , psychology , mathematical analysis , psychotherapist , operating system
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.