Fuzzy Series Application for Decision Making

In today’s complex and uncertain world, decision-making often involves ambiguity, subjectivity, and incomplete information. Traditional binary logic is no longer sufficient to address these challenges. This course introduces Fuzzy Logic, an advanced approach that mimics human reasoning and enables more flexible, realistic, and intelligent decision-making.

Developed from the pioneering work of Lotfi A. Zadeh, fuzzy logic allows systems to process vague and linguistic information such as “high,” “medium,” or “low,” making it highly applicable across engineering, business, artificial intelligence, and sustainability domains.

This course provides a comprehensive and practical learning experience, starting from fundamental concepts of fuzzy sets and membership functions, progressing to fuzzy inference systems, and advancing to real-world applications in decision-making models such as MCDM (Multi-Criteria Decision Making). Learners will gain hands-on experience in building fuzzy systems and applying them to real cases, including ESG evaluation, halal supply chain management, and intelligent business systems.

Designed for students, researchers, and professionals, this course bridges theoretical knowledge and practical implementation, empowering learners to develop intelligent models that handle uncertainty effectively.

By the end of the course, participants will be able to design fuzzy systems, analyze complex problems, and apply fuzzy logic techniques to support strategic and data-driven decisions in various industries.