Generative Artificial Intelligence (GAI) telah memegang penting dalam berbagai bidang, termasuk sebagai alat bantu pemrograman di Indonesia. Namun, penelitian mengenai adopsi GAI sebagai alat bantu pemrograman masih terbatas. Penelitian ini bertujuan menganalisis faktor yang memengaruhi niat karyawan di Indonesia untuk mengadopsi GAI dalam pemrograman, dengan fokus pada kualitas output kode dan kualitas sistem yang memengaruhi persepsi kegunaan serta kemudahan penggunaan GAI. Penelitian menggunakan metode PLS-SEM dalam analisis kuantitatif dengan 497 data valid, serta analisis kualitatif melalui wawancara 10 narasumber. Hasilnya menunjukkan bahwa persepsi kegunaan dipengaruhi oleh faktor presentation, structure, interactivity, responsiveness, understandability, assurance, dan reliability, sementara persepsi kemudahan penggunaan dipengaruhi oleh presentation, structure, responsiveness, assurance, dan reliability. Kedua persepsi ini memengaruhi niat adopsi GAI untuk pemrograman. Penelitian juga meneliti hubungan ini berdasarkan gender dan usia melalui analisis multigrup. Hasilnya memberikan saran bagi pengembang GAI untuk meningkatkan kualitas kode output dan sistem, yang terbukti memengaruhi persepsi pengguna tentang kegunaan dan kemudahan penggunaan GAI

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Generative Artificial Intelligence (GAI) has become significant in various fields, including as a programming aid in Indonesia. However, research on the adoption of GAI as a programming tool remains limited. This study aims to analyze the factors influencing employees in Indonesia to adopt GAI for programming, focusing on output code quality and system quality, which affect the perceived usefulness and ease of use of GAI. The study employs the PLS-SEM method for quantitative analysis with 497 valid data points and qualitative analysis through interviews with 10 informants. The results indicate that perceived usefulness is influenced by factors such as presentation, structure, interactivity, responsiveness, understandability, assurance, and reliability, while perceived ease of use is influenced by presentation, structure, responsiveness, assurance, and reliability. Both perceptions affect the intention to adopt GAI for programming. The study also examines these relationships based on gender and age using multigroup analysis. The findings provide practical suggestions for GAI developers to enhance the quality of output code and system, which significantly influence users' perceptions of the usefulness and ease of use of GAI.