Kusuma, Serafaldo (2026) Analisis Faktor-Faktor yang Memengaruhi Behavioral Intention dalam Teknologi AI untuk Quality Inspection dengan Technology Acceptance Model pada PT XYZ. Masters thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Perkembangan teknologi Artificial Intelligence (AI) memberikan peluang besar bagi industri manufaktur untuk meningkatkan efisiensi dan akurasi quality inspection. Penerapan AI dalam quality inspection diharapkan dapat mengurangi kesalahan manusia dan mempercepat pengambilan keputusan. Namun, keberhasilan penerapan teknologi tersebut sangat bergantung pada intensi pengguna di lingkungan kerja. Banyak inisiatif digital tidak berjalan optimal karena rendahnya persepsi manfaat dan kemudahan penggunaan oleh karyawan. Penelitian ini penting dilakukan untuk memahami faktor-faktor yang memengaruhi penerimaan pengguna terhadap AI dalam quality inspection, sehingga perusahaan dapat mengembangkan strategi implementasi yang lebih efektif. Pendekatan yang dilakukan adalah Technology Acceptance Model (TAM) dengan variabel perceived usefulness (PU), perceived ease of use (PEU), perceived enjoyment (PE), perceived cyber risk (PCR), perceived innovativeness in IT (PIIT), self efficacy (SE) dan behavioral intention (BI). Penelitian dilakukan dengan pendekatan kuantitatif melalui penyebaran kuesioner di PT XYZ kepada karyawan yang terlibat langsung dalam inspeksi kualitas. Hasil penelitian menggunakan metode PLS-SEM menunjukkan bahwa variabel perceived usefulness (PU) memiliki signifikansi terbesar mempengaruhi behavioral intention (BI). Strategi peningkatan penerimaan teknologi oleh perusahaan dapat difokuskan pada variabel prioritas yang berdampak besar, salah satunya yaitu dengan cara pemberian training dan pemahaman kepada karyawan terkait manfaat AI yang dapat membantu kinerja.
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Artificial Intelligence (AI) offers significant potential for the manufacturing industry to enhance efficiency and accuracy in quality inspection. Its implementation is expected to reduce human errors and accelerate decision-making. However, the success of AI adoption depends greatly on user intention within the organization. Many digital initiatives fail due to low perceptions of usefulness and ease of use among employees. This study aims to analyze user intention of AI in quality inspection using the Technology Acceptance Model (TAM), which consists of perceived usefulness (PU), perceived ease of use (PEU), perceived enjoyment (PE), perceived cyber risk (PCR), perceived innovativeness in IT (PIIT), self efficacy (SE) and behavioral intention (BI). A quantitative approach is applied through questionnaires distributed to employees at PT XYZ that directly involved in quality inspection activities. The results obtained using the PLS-SEM method indicate that perceived usefulness (PU) has the most significant influence on behavioral intention (BI). Based on these findings, companies are encouraged to prioritize strategies that enhance key influencing factors, particularly by providing training and improving employees’ understanding of AI benefits to support their work performance.
| Item Type: | Thesis (Masters) |
|---|---|
| Uncontrolled Keywords: | Artificial Intelligence, Quality Inspection, Technology Acceptance Model (TAM), Artificial Intelligence, Quality Inspection, Technology Acceptance Model (TAM) |
| Subjects: | T Technology > T Technology (General) > T58.6 Management information systems |
| Divisions: | 61101-Magister Management Technology |
| Depositing User: | Serafaldo Angga Kusuma |
| Date Deposited: | 28 Jul 2026 00:54 |
| Last Modified: | 28 Jul 2026 00:54 |
| URI: | http://repository.its.ac.id/id/eprint/137912 |
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