Factors Influencing User Satisfaction with Generative Artificial Intelligence Power Chat System

This research aims to explore the factors that affect user satisfaction with AI chat systems, particularly within the Indonesian context, to create a comprehensive evaluation scale for user experience. A quantitative approach using surveys with a Likert scale model was employed. Questionnaires were distributed online to AI chat users in Indonesia. A total of 365 valid questionnaires were collected, and all items were recorded using a seven-point Likert scale. Factor analysis was adopted to identify user satisfaction. Then, multiple regressions analysis was used to examine the impact of the multiple factors on AI chat system user satisfaction. The data analysis identifies factors that directly affect user satisfaction with the Generative Artificial Intelligence Powered Chat System. These factors are credibility, interactivity, ease of use, usefulness, convenience, growth, logical inference, and enjoyment. In contrast, the factors that indirectly affect user satisfaction are security, creativity, anthropomorphism, and accuracy. This study aims to provide valuable insights that will inform the design and implementation of more effective and user-friendly AI chat technology.