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All Journal West Science Social and Humanities Studies Advance Sustainable Science, Engineering and Technology (ASSET)
Supiah Ningsih
Universitas Muhammadiyah Asahan
Humanities Chemistry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Public Health Social Sciences

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The Influence of AI Ethics in HR and Algorithm Transparency on Employee Trust in the Manufacturing Industry Supiah Ningsih; Danil Syahputra; Nazifah Husainah; Adityo Ari Wibowo; Cikita Berlian Hakim
West Science Social and Humanities Studies Vol. 4 No. 03 (2026): West Science Social and Humanities Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsshs.v4i03.2702

Abstract

This study examines the influence of artificial intelligence (AI) ethics in human resources and algorithm transparency on employee trust in the manufacturing industry. The rapid adoption of AI in organizational management has transformed HR practices, including recruitment, performance evaluation, and workforce management, by enabling more efficient and data-driven decision-making. However, the use of AI also raises concerns regarding ethical governance and the transparency of algorithmic decision-making processes. This research employs a quantitative approach using a survey method involving 150 employees working in manufacturing companies. Data were collected through structured questionnaires measured on a five-point Likert scale and analyzed using Structural Equation Modeling with Partial Least Squares (SEM-PLS 3). The results indicate that AI ethics in HR has a positive and significant effect on employee trust, suggesting that the application of ethical principles in AI-based HR practices enhances employees’ perceptions of fairness and organizational responsibility. In addition, algorithm transparency also shows a positive and significant influence on employee trust, demonstrating that clear explanations of AI decision-making processes can increase employees’ confidence in technology-driven HR systems. The structural model reveals that both variables explain 63% of the variance in employee trust (R² = 0.63). Overall, these findings emphasize the importance of responsible AI governance and transparent algorithmic systems in strengthening employee trust and supporting the sustainable adoption of AI technologies within organizations.
Integrating Digital Technologies for Sustainable Tourism: Quantitative Assessment of Tech-Enabled Organizational Practices Supiah Ningsih; Rudy Irwansyah; Danil Syahputra; Inda Arfa Syera; Muhammad Arief Tirtana
Advance Sustainable Science Engineering and Technology Vol. 8 No. 2 (2026): February-April
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i2.2589

Abstract

This study examines how digital transformation technologies drive sustainability performance in the tourism sector by integrating Internet of Things (IoT), artificial intelligence (AI), and big data analytics into organizational culture and leadership. A mixed dataset of 300 tourism enterprises in Asahan Regency, Indonesia, complemented by technical indicators such as energy consumption (kWh) and IoT penetration, was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that Tech-Enabled Organizational Culture (TE-OC) (β = 0.487, p < 0.001) and Tech-Enabled Green Leadership (TE-GL) (β = 0.531, p < 0.001) significantly influence Smart Green Culture (SGC), which has the strongest effect on Technology-Supported Sustainable Tourism Performance (TS-STP) (β = 0.664, p < 0.001; R² = 0.651). While the direct effects of TE-OC and TE-GL on TS-STP are limited, their indirect effects through SGC are substantial, indicating that digitally enabled culture plays a key mediating role. The findings suggest that competitiveness in sustainable tourism depends not only on managerial orientation but also on measurable investments in digital technologies. Limitations include the cross-sectional design and reliance on self-reported data; future research should incorporate longitudinal sensor-based data and comparative analyses across destinations.
Co-Authors Adityo Ari Wibowo Cikita Berlian Hakim Danil Syahputra Irwansyah, Rudy Muhammad Arief Tirtana Nazifah Husainah Syera, Inda Arfa