COMPARISON OF FUZZY LOGIC IMPLEMENTATION AND SAW IN DECISION SUPPORT SYSTEM STRATEGIC FUNCTION AND INNOVATION: A SYSTEMATIC LITERATURE STUDY

Abstract

The study compares the implementation of Fuzzy Logic and Simple Additive Weighting (SAW) in Decision Support System (DSS) strategic and innovation functions through a systematic literature study. Fuzzy Logic and SAW are two techniques that are often used in DSS to support complex and multi criteria decision making. However, there is a need to understand the advantages and limitations of each method in the context of DSS, especially in terms of accuracy, flexibility, and the ability to handle uncertainty. The main focus of this study is to analyze the strategic and innovation functions produced by both methods. The purpose of this study is to provide in-depth insight into the conditions and situations where one method is superior to the other, as well as to provide recommendations for the development of a more effective and innovative DSS. This literature study collects and evaluates various studies that discuss the application of Fuzzy Logic and SAW in the context of DSS. A systematic approach is used to identify, select, and analyze relevant literature, to ensure that the findings are based on strong and reliable evidence. The results show that Fuzzy Logic and SAW have their respective advantages and limitations in terms of accuracy, flexibility, and the ability to handle uncertainty. This research provides recommendations for the development of more effective and innovative DSS.