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All Journal Aptisi Transactions on Technopreneurship (ATT) ADI Journal on Recent Innovation (AJRI)
Ayubi, M. Nizar
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Religion Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Economics, Econometrics & Finance Education Industrial & Manufacturing Engineering Social Sciences

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Optimizing Learning Experiences: A Study of Student Satisfaction with LMS in Higher Education Ayubi, M. Nizar; Retnowardhani, Astari
Aptisi Transactions On Technopreneurship (ATT) Vol 7 No 2 (2025): July
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/att.v7i2.501

Abstract

This research delves into the examination of student satisfaction regarding the use of Learning Management Systems (LMS) through a comprehensive questionnaire distributed among 326 participants. The study adopts a modified DeLone and McLean is Model as its methodology to assess various dimensions of LMS satisfaction. Utilizing SmartPLS for hypothesis testing, the study rigorously analyzes the data collected. The findings indicate the acceptance of all proposed hypotheses, revealing significant correlations among the variables under scrutiny. A notable outcome is the identification of service quality as the most prominent influencer of student satisfaction within LMS environments. This underscores the critical imperative for higher education institutions to prioritize and address service quality concerns proactively. Practical solutions may encompass optimizing technical support structures, refining user interfaces for enhanced accessibility, ensuring system stability, and facilitating ongoing training and support initiatives. By addressing these pivotal areas, institutions can elevate the overall student learning experience and enhance the efficacy of LMS platforms in facilitating robust educational outcomes.
Decentralized Decision Intelligence Using AI and Blockchain in Modern Enterprises Ayubi, M. Nizar; Anggoro, Sigit; Kareem, Yasir Mustafa
ADI Journal on Recent Innovation Vol. 7 No. 1 (2025): September
Publisher : ADI Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/ajri.v7i1.1320

Abstract

In the era of digital transformation, enterprises face increasing pressure to enhance transparency, operational efficiency, and trust in their decision making processes, especially in complex, data-intensive environments. While prior studies have separately explored the roles of Artificial Intelligence (AI) and Blockchain, few have examined their combined impact in creating decentralized and intelligent decision systems within real enterprise contexts. This study introduces a novel conceptual integration model that merges AI-driven analytics with blockchain-based validation mechanisms to enable transparent, traceable, and autonomous decision-making. By synthesizing AI predictive and analytical capabilities with blockchain immutable and distributed architecture, this research extends recent studies (2021-2025) by demonstrating how such convergence can eliminate central dependencies, enhance digital trust, and support data governance across departments. A qualitative case study approach was used to analyze organizations adopting AI blockchain frameworks, and the findings reveal new insights on interoperability, adaptive governance, and smart contract-driven autonomy. The study originality lies in its emphasis on the AI Blockchain synergy as a unified decision-intelligence infrastructure, contributing to the growing discourse on ethical and resilient enterprise systems.
Co-Authors Anggoro, Sigit Kareem, Yasir Mustafa Retnowardhani, Astari