This research discusses the development of a recommendation information system to make it easier for customers to select and purchase Klampar batik in Pamekasan. This process is often complicated because it involves many factors such as various motifs, quality and prices of batik on the market. To overcome this challenge, we developed a chatbot-based system using the Chatbase Website platform. This approach involves a preliminary study to identify customer problems, an analysis of their needs, and a literature review of current recommendation systems and chatbot technology. This research designs the architecture of a web-based chatbot system, determines a recommendation algorithm based on customer preferences, and integrates a database containing information on various motifs, prices and quality of Klampar batik. Next, build a user-friendly website and chatbot, train a recommendation model with historical customer data, and integrate the system with social media and popular messaging services to reach more customers. This research conducts system testing to ensure optimal performance and evaluates customer responses to chatbot recommendations. The results show that customers feel more confident in choosing Klampar batik after using this system. Additionally, the system also provides manufacturers with insight into customer preferences, which can be used to improve their production and offerings. This research concludes that the development of a chatbot-based Klampar batik recommendation information system with the Chatbase Website can overcome initial problems in selecting batik in Pamekasan.