Loren, Friska (2025) Analisis behavioral intention dosen di Indonesia dalam menggunakan generative ai tools untuk pengajaran dan pembelajaran berdasarkan tam. Bachelor thesis, Universitas Pelita Harapan.
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Abstract
Penggunaan Generative AI dalam pendidikan tinggi semakin berkembang, namun adopsinya di kalangan dosen Indonesia masaih menghadapi berbagai tantangan. Penelitian ini memiliki tujuan untuk menganalisis faktor-faktor apa saja yang memiliki pengaruh terhadap niat dosen dalam menggunakan Generative AI tools berdasarkan Technology Acceptance Model (TAM), dengan variabel tambahan kepercayaan, persepsi kecemasan, dan persepsi risiko. Metode penelitian yang dipilih adalah pendekatan kuantitatif dengan penyebaran kuesioner secara online. Sebanyak 345 responden diperoleh dan data dianalisis dengan SEM-PLS melalui software SmartPLS. Hasil penelitian menunjukkan bahwa enam dari delapan hipotesis dapat diterima, dengan nilai t-statistics dan p-value untuk variabel T dan PEU (16,884; 0,000), T dan PU (3,879; 0,000), PA dan PU (3,414; 0,001), PEU dan PU (7,670; 0,000), PEU dan BI (4,322; 0,000), serta PU dan BI (6,595; 0,000). Sedangkan untuk hipotesis yang ditolak, meliputi variabel PA dan PEU (0,114; 0,909), serta PR dan PU (1,040; 0,298). Dengan demikian, temuan ini menegaskan pentingnya membangun kepercayaan serta mengurangi kecemasan dosen dalam menggunakan Generative AI untuk meningkatkan niat penggunaannya di ruang lingkup pendidikan tinggi. / The use of Generative AI in higher education is growing rapidly, yet its adoption among Indonesian lecturers still faces several challenges. This study aims to examine the factors influencing lecturers' intention to use Generative AI tools, employing the Technology Acceptance Model (TAM) with additional variables: trust, perceived anxiety, and perceived risk. A quantitative approach was used by distributing an online questionnaire. A total of 345 responses were collected and analyzed using SEM-PLS via SmartPLS software. The results show that six out of eight hypotheses were accepted, with t-statistics dan p-values for the variables T and PEU (16.884; 0.000), T and PU (3.879; 0.000), PA and PU (3.414; 0.001), PEU and PU (7.670; 0.000), PEU and BI (4.322; 0.000), and PU and BI (6.595; 0.000). Meanwhile, the rejected hypotheses involve the relationships between PA and PEU (0.114; 0.909), and PR and PU (1.040; 0.298). Therefore, the outcomes of this study highlight the importance of building trust and reducing anxiety among lecturers to improve the adoption of Generative AI tools within higher education.
Item Type: | Thesis (Bachelor) |
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Creators: | Creators NIM Email ORCID Loren, Friska NIM03081210019 friskaloren@gmail.com UNSPECIFIED |
Contributors: | Contribution Contributors NIDN/NIDK Email Thesis advisor Barus, Okky Putra NIDN0127068803 okky.barus@uph.edu |
Uncontrolled Keywords: | dosen; generative ai; pendidikan tinggi; technology acceptance model (tam); behavioral intention; trust; perceived anxiety; perceived risk |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | University Subject > Current > Faculty/School - UPH Medan > School of Information Science and Technology > Information Systems Current > Faculty/School - UPH Medan > School of Information Science and Technology > Information Systems |
Depositing User: | Friska Loren |
Date Deposited: | 22 Jul 2025 06:30 |
Last Modified: | 22 Jul 2025 06:30 |
URI: | http://repository.uph.edu/id/eprint/69978 |