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All Journal International Journal of Education, Social Studies, And Management (IJESSM)
Abd Rifai
Universitas Gorontalo, Indonesia
Education Other

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The Influence of the UTAUT Model on the Adoption of Artificial Intelligence in the Personnel Management System of the Tojo Una-Una Regency Government Abd Rifai; Idrus Usu; Moh Afan Suyanto
International Journal Of Education, Social Studies, And Management (IJESSM) Vol. 6 No. 1 (2026): The International Journal of Education, Social Studies, and Management (IJESSM)
Publisher : LPPPIPublishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52121/ijessm.v6i1.1059

Abstract

This study aims to identify and analyze the influence of the Unified Theory of Acceptance and Use of Technology (UTAUT) model factors, consisting of Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions, on the adoption of Artificial Intelligence (AI) within the personnel management system of the Government of Tojo Una-Una Regency. This study employed a quantitative approach using a survey method involving 87 respondents, consisting of employees of BKPSDMD and Heads of Personnel Subdivisions of regional government agencies in Tojo Una-Una Regency. Data collection was conducted through questionnaire distribution and analyzed using multiple linear regression with the assistance of SPSS version 31.0. The results indicate that, partially, Performance Expectancy and Effort Expectancy have a positive and significant effect on Behavioral Intention toward AI adoption, while Social Influence and Facilitating Conditions do not have a significant effect. Simultaneously, all variables within the UTAUT model significantly influence Behavioral Intention toward AI adoption. The coefficient of determination (R²) value of 0.702 indicates that the independent variables are able to explain 70.2% of the variation in Behavioral Intention. This study demonstrates that the perceived usefulness and ease of use of technology are the primary factors influencing employees’ intentions to adopt Artificial Intelligence technology.
Co-Authors Idrus Usu Moh Afan Suyanto