Application of Fuzzy Matching in chatbot development to improve user experience on e-commerce sites (Case study: Cutiw Fashion Store) - Syifa Rahma Nisa; Rionaldi Ali (Goodwood Publishing, 2025)
Purpose: In the rapidly developing digital era, e-commerce websites face challenges in providing responsive and personalized customer service. This study aims to develop a web-based chatbot for the Fashion Cutiw Store by implementing the Fuzzy String Matching method to enhance user experience. Methods: The research involves designing and implementing a web-based chatbot integrated with the Fuzzy String Matching method. This approach enables the chatbot to understand and respond to customer inquiries despite variations in wording or typographical errors, thereby improving the accuracy and relevance of responses. Results: The evaluation results indicate that the chatbot employing Fuzzy String Matching successfully improves user satisfaction through more natural and efficient interactions. The chatbot is able to deliver product information quickly and accurately while handling diverse user input formats. Conclusions: The implementation of a web-based chatbot using the Fuzzy String Matching method effectively enhances customer service performance in e-commerce. It reduces reliance on manual customer support and provides faster, more reliable responses to customer inquiries. Limitation: This study is limited to a single e-commerce platform and focuses primarily on text-based interactions. The chatbot’s performance may vary when handling complex queries or expanding to other product categories without further training and development. Contribution: This research contributes to the development of adaptive automated customer service systems in the e-commerce sector, demonstrating the effectiveness of Fuzzy String Matching in improving chatbot responsiveness and user experience.