AI adoption readiness in universities: A multivariate regression and machine learning analysis of Malaysia and Indonesia

This study investigates the determinants of AI adoption in higher education institutions in Malaysia and Indonesia using an integrated analytical framework that combines behavioral, institutional, and training-related factors. A quantitative cross-sectional survey was conducted in 2025, yielding 748...

Full description

Saved in:
Bibliographic Details
Main Authors: Othman, Mohd Azlishah, Ja'afar, Abd Shukur, Abdul Manap, Redzuan, Misran, Mohamad Harris, Meor Said, Maizatul Alice, Suhaimi, Shadia, Hassan, Nurmala Irdawaty, Nugraha, Yoga Tri
Format: Article
Language:en
Published: Research and Scientific Innovation Society 2026
Online Access:http://eprints.utem.edu.my/id/eprint/29497/2/00645210120261117342940.pdf
http://eprints.utem.edu.my/id/eprint/29497/
https://rsisinternational.org/journals/ijriss/article.php?id=4625
https://doi.org/10.47772/IJRISS.2025.91200317
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1858062961603510272
author Othman, Mohd Azlishah
Ja'afar, Abd Shukur
Abdul Manap, Redzuan
Misran, Mohamad Harris
Meor Said, Maizatul Alice
Suhaimi, Shadia
Hassan, Nurmala Irdawaty
Nugraha, Yoga Tri
author_facet Othman, Mohd Azlishah
Ja'afar, Abd Shukur
Abdul Manap, Redzuan
Misran, Mohamad Harris
Meor Said, Maizatul Alice
Suhaimi, Shadia
Hassan, Nurmala Irdawaty
Nugraha, Yoga Tri
author_sort Othman, Mohd Azlishah
building UTEM Library
collection Institutional Repository
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
continent Asia
country Malaysia
description This study investigates the determinants of AI adoption in higher education institutions in Malaysia and Indonesia using an integrated analytical framework that combines behavioral, institutional, and training-related factors. A quantitative cross-sectional survey was conducted in 2025, yielding 748 valid responses from academic staff and students (response rate: 34%). The analysis employed logistic regression, ordinal regression, structural path modeling, heatmap segmentation, and machine learning clustering. Results demonstrate that perceived ease of use and perceived usefulness are the strongest predictors of AI usage and user satisfaction, with standardized effects exceeding those of demographic variables. AI training significantly increases adoption likelihood, raising sustained AI usage probability by over 40% among trained participants. Malaysian institutions exhibit higher adoption maturity, with AI training participation of 68.3% compared to 54.1% in Indonesian institutions. However, satisfaction levels in both countries remain largely neutral to moderate, indicating that AI integration is still at a transitional stage. Compared with prior research, this study advances understanding of AI adoption by integrating advanced statistical modeling with machine learning methods, offering stronger empirical evidence for policy design and leadership decision-making in higher education.
format Article
id my.utem.eprints-29497
institution Universiti Teknikal Malaysia Melaka
language en
publishDate 2026
publisher Research and Scientific Innovation Society
record_format eprints
spelling my.utem.eprints-294972026-02-23T01:20:38Z http://eprints.utem.edu.my/id/eprint/29497/ AI adoption readiness in universities: A multivariate regression and machine learning analysis of Malaysia and Indonesia Othman, Mohd Azlishah Ja'afar, Abd Shukur Abdul Manap, Redzuan Misran, Mohamad Harris Meor Said, Maizatul Alice Suhaimi, Shadia Hassan, Nurmala Irdawaty Nugraha, Yoga Tri This study investigates the determinants of AI adoption in higher education institutions in Malaysia and Indonesia using an integrated analytical framework that combines behavioral, institutional, and training-related factors. A quantitative cross-sectional survey was conducted in 2025, yielding 748 valid responses from academic staff and students (response rate: 34%). The analysis employed logistic regression, ordinal regression, structural path modeling, heatmap segmentation, and machine learning clustering. Results demonstrate that perceived ease of use and perceived usefulness are the strongest predictors of AI usage and user satisfaction, with standardized effects exceeding those of demographic variables. AI training significantly increases adoption likelihood, raising sustained AI usage probability by over 40% among trained participants. Malaysian institutions exhibit higher adoption maturity, with AI training participation of 68.3% compared to 54.1% in Indonesian institutions. However, satisfaction levels in both countries remain largely neutral to moderate, indicating that AI integration is still at a transitional stage. Compared with prior research, this study advances understanding of AI adoption by integrating advanced statistical modeling with machine learning methods, offering stronger empirical evidence for policy design and leadership decision-making in higher education. Research and Scientific Innovation Society 2026 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/29497/2/00645210120261117342940.pdf Othman, Mohd Azlishah and Ja'afar, Abd Shukur and Abdul Manap, Redzuan and Misran, Mohamad Harris and Meor Said, Maizatul Alice and Suhaimi, Shadia and Hassan, Nurmala Irdawaty and Nugraha, Yoga Tri (2026) AI adoption readiness in universities: A multivariate regression and machine learning analysis of Malaysia and Indonesia. International Journal of Research and Innovation in Social Science (IJRISS), IX (XII). pp. 4022-4030. ISSN 2454-6186 https://rsisinternational.org/journals/ijriss/article.php?id=4625 https://doi.org/10.47772/IJRISS.2025.91200317
spellingShingle Othman, Mohd Azlishah
Ja'afar, Abd Shukur
Abdul Manap, Redzuan
Misran, Mohamad Harris
Meor Said, Maizatul Alice
Suhaimi, Shadia
Hassan, Nurmala Irdawaty
Nugraha, Yoga Tri
AI adoption readiness in universities: A multivariate regression and machine learning analysis of Malaysia and Indonesia
title AI adoption readiness in universities: A multivariate regression and machine learning analysis of Malaysia and Indonesia
title_full AI adoption readiness in universities: A multivariate regression and machine learning analysis of Malaysia and Indonesia
title_fullStr AI adoption readiness in universities: A multivariate regression and machine learning analysis of Malaysia and Indonesia
title_full_unstemmed AI adoption readiness in universities: A multivariate regression and machine learning analysis of Malaysia and Indonesia
title_short AI adoption readiness in universities: A multivariate regression and machine learning analysis of Malaysia and Indonesia
title_sort ai adoption readiness in universities: a multivariate regression and machine learning analysis of malaysia and indonesia
url http://eprints.utem.edu.my/id/eprint/29497/2/00645210120261117342940.pdf
http://eprints.utem.edu.my/id/eprint/29497/
https://rsisinternational.org/journals/ijriss/article.php?id=4625
https://doi.org/10.47772/IJRISS.2025.91200317
url_provider http://eprints.utem.edu.my/