Akselerasi learning curve dengan generative ai untuk meningkatkan produktivitas karyawan fresh graduate (studi tam)

Chai, Christopher Alexander (2024) Akselerasi learning curve dengan generative ai untuk meningkatkan produktivitas karyawan fresh graduate (studi tam). Bachelor thesis, Universitas Pelita Harapan.

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Abstract

Generative AI semakin banyak digunakan dalam dunia kerja untuk meningkatkan produktivitas dan mempercepat adaptasi karyawan baru. Penelitian ini bertujuan untuk menganalisis bagaimana Generative AI dapat mempercepat learning curve dan meningkatkan produktivitas karyawan fresh graduate dengan menggunakan kerangka kerja Technology Acceptance Model (TAM). Penelitian ini dilakukan secara kuantitatif dengan melibatkan karyawan fresh graduate dari berbagai universitas di Medan sebagai responden. Metode Structural Equation ModelingPartial Least Squares (SEM-PLS) digunakan untuk menganalisis data, khususnya dalam menguji hubungan antara persepsi kemudahan penggunaan dan persepsi kegunaan terhadap akselerasi learning curve serta dampaknya pada produktivitas. Hasil penelitian menunjukkan bahwa persepsi kemudahan penggunaan dan persepsi kegunaan Generative AI memiliki pengaruh signifikan dalam mempercepat learning curve, yang selanjutnya berdampak positif pada peningkatan produktivitas karyawan fresh graduate. Temuan ini memberikan implikasi penting bagi perusahaan dalam mendukung adopsi teknologi AI serta bagi pengambil kebijakan untuk mendukung pelatihan terkait AI dalam kurikulum pendidikan tinggi. / Generative AI is increasingly utilized in the workplace to enhance productivity and accelerate the adaptation of new employees. This study aims to analyze how Generative AI can accelerate the learning curve and improve productivity among fresh graduate employees using the Technology Acceptance Model (TAM) framework. This quantitative research involves fresh graduate employees from various universities in Medan as respondents. The data is analyzed using Structural Equation Modeling-Partial Least Squares (SEM-PLS) to examine the relationships between perceived ease of use, perceived usefulness, and learning curve acceleration and its impact on productivity. The results indicate that the perceived ease of use and usefulness of Generative AI significantly influence the acceleration of the learning curve, which subsequently has a positive effect on fresh graduate employee productivity. These findings have important implications for companies in supporting AI technology adoption and for policymakers in endorsing AI-related training within higher education curricula.
Item Type: Thesis (Bachelor)
Creators:
Creators
NIM
Email
ORCID
Chai, Christopher Alexander
NIM03081210007
chris310803@gmail.com
UNSPECIFIED
Contributors:
Contribution
Contributors
NIDN/NIDK
Email
Thesis advisor
Barus, Okky Putra
NIDN0127068803
okky.barus@uph.edu
Uncontrolled Keywords: Generative AI; produktivitas, akselerasi learning curve; fresh graduate; Technology Acceptance Model; SEM-PLS
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Depositing User: christopher chai
Date Deposited: 25 Feb 2025 03:40
Last Modified: 25 Feb 2025 03:40
URI: http://repository.uph.edu/id/eprint/67232

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