Application of Fuzzy Logic in Predictive Analytics for E-Commerce Transaction Data

Our objective is to identify the key factors that influence e-commerce success by analyzing transactional data, including variables such as product descriptions, quantities, unit prices, and customer demographics. We have employed three distinct fuzzy logic methods: TOPSIS, Fuzzy AHP (F-AHP), and F-AHP enhanced by geometric mean. These methods have been utilized to rank various factors, ultimately identifying the most critical elements for optimizing inventory management, enhancing customer satisfaction, and detecting fraudulent activities in the e-commerce landscape. The results provide valuable insights for developing smarter decision-making practices in e-commerce operations.