Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Journal of Education and Teaching Learning International Journal of Computer Technology and Science
Aziz Azindani
Unknown Affiliation
Computer Science & IT Other

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
A Scalable Human Centered Artificial Intelligence Architecture for Decision Support Systems in Large Scale Digital Transformation Ecosystems Aziz Azindani; Ismi Kusumaningroem; Ilham Akhsani
International Journal of Computer Technology and Science Vol. 1 No. 1 (2024): International Journal of Computer Technology and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijcts.v1i1.360

Abstract

Artificial Intelligence (AI)-based Decision Support Systems (DSS) have become a central component of digital transformation initiatives across various industries. While prior studies have primarily emphasized technical aspects such as accuracy, performance, and computational efficiency, less attention has been given to the integration of human-centered principles and scalable architectural design. This study aims to examine how AI-based DSS can be enhanced through the combined application of Human-Centered Artificial Intelligence (HCAI) principles and scalable AI architecture. Using a qualitative, literature-based research methodology, this study systematically analyzes peer-reviewed publications indexed in Scopus to identify key dimensions influencing the effectiveness and sustainability of AI-driven DSS. The findings indicate that technical capabilities alone are insufficient to ensure successful adoption and long term impact. Instead, transparency, explainability, ethical governance, and user empowerment core elements of HCAI are critical for fostering trust and user acceptance. Furthermore, scalable architectural principles, including modularity, interoperability, and adaptability, are essential for enabling AI-based DSS to operate reliably in large-scale and dynamic environments. This study contributes a unified conceptual framework that bridges technical scalability and human-centered design, offering theoretical insights and practical guidance for developing trustworthy, scalable, and sustainable AI-based Decision Support Systems in digital transformation contexts.
Beyond Digital Access: Generative Artificial Intelligence and Digital Literacy Predict Vocational Students’ Academic Writing Ria Ria Candra Dewi; Aziz Azindani; Lily Budinurani; Novita Wulandari
Journal of Education and Teaching Learning Vol.4 No.1 July (2026)
Publisher : PT MEDIA JURNAL DAN PENDIDIKAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59211/mjpjetl.v4i1.392

Abstract

This study examined the partial and simultaneous statistical effects of digital literacy and responsible generative artificial intelligence utilization on vocational students’ academic writing skills. A quantitative explanatory-correlational approach with a cross-sectional survey design was employed. The sample comprised 100 students from five vocational study programs selected through proportionate stratified random sampling. Data were collected using two 10-item Likert questionnaires measuring digital literacy and generative artificial intelligence utilization, together with a source-based academic essay performance test assessed using an analytic rubric. Pearson correlation and multiple linear regression were applied. Digital literacy had a positive and significant statistical effect on academic writing skills (B = 6.413; β = 0.334; p < 0.001). Generative artificial intelligence utilization also had a positive and significant effect and provided a stronger relative contribution (B = 9.097; β = 0.494; p < 0.001). Simultaneously, both predictors produced F(2,97) = 42.013; p < 0.001 and explained 46.4% of the variance. These findings indicated that vocational students’ academic writing development required the integration of digital literacy and critical, ethical, and responsible artificial intelligence practices in writing instruction and institutional policy.
Co-Authors Akhsani, Ilham Ismi Kusumaningroem, Ismi Lily Budinurani NOVITA WULANDARI Ria Ria Candra Dewi