User Satisfaction Evaluation of Meta AI Integration in WhatsApp: A Quantitative EUCS Approach

Pratama Angga Buana (Universitas Semarang)
Yekti Adi Prasetyo (Universitas Semarang)
Muhammad Muhsinin (Universitas Semarang)
Muhammad Said Riza (Universitas Semarang)
Ahmad Maulana Arif (Universitas Semarang)
Andika Timur Prakoso (Universitas Semarang)

Journal of Information Technology, Computer Engineering and Artificial Intelligence (ITCEA)
Vol. 1 No. 2 (2024): Journal of Information Technology, Computer Engineering and Artificial Intellig

This study aims to evaluate user satisfaction with the integration of Meta AI technology in the WhatsApp application using the End User Computing Satisfaction (EUCS) model. The model encompasses five key dimensions: Content, Accuracy, Format, Ease of Use, and Timeliness. Data was collected through questionnaires distributed to 44 respondents consisting of students, with the sample determined using the Slovin formula. The analysis revealed that overall user satisfaction falls into the "Satisfied" category, with the highest average score in the Content dimension (3.83) and the lowest in the Ease of Use dimension (3.45). The Ease of Use dimension requires special attention, as some users find Meta AI's navigation challenging. This study contributes to the development of Meta AI features in WhatsApp and serves as a reference for future studies focusing on user satisfaction evaluation