Analisis Kepuasan Pengguna Meta AI Instagram Dengan Model TAM-EUCS

Abstract

Meta AI is a feature of artificial intelligence created by Meta Inc to assist users in generating content and acquiring information in an interactive manner. This research seeks to assess user satisfaction with the Meta AI feature by employing a combined methodology of the Technology Acceptance Model and End User Computing Satisfaction. The research included 403 participants who actively use Instagram and have utilized the Meta AI feature. The analysis technique employed was Partial Least Squares Structural Equation Modeling to investigate the impact of seven independent variables on user attitude and the effect of user attitude on user satisfaction. The findings indicated that perceived usefulness, perceived ease of use, and format significantly influence user attitude, whereas content, accuracy, technical ease, and timeliness do not show a notable impact. Moreover, user perception significantly impacts user satisfaction. Ultimately, perceived advantages, accessibility, and visual layout are the primary elements influencing user perceptions and contentment regarding AI-driven functionalities on social media.