Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE)
Wasesa, Istikha Ruchitra Hayudirga
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Integration of Artificial Intelligence in Management Information Systems to Improve the Effectiveness of Strategic Decision-Making in the Digital Era Wasesa, Istikha Ruchitra Hayudirga; Permatasari, Dhyta; Angkat, Fhatiya Alzahra; Al-Khowarizmi, Al-Khowarizmi
Journal of Computer Science, Information Technology and Telecommunication Engineering Vol 6, No 2 (2025)
Publisher : Universitas Muhammadiyah Sumatera Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/jcositte.v6i2.26051

Abstract

The integration of Artificial Intelligence (AI) into Management Information Systems (MIS) has emerged as a strategic imperative for enhancing the effectiveness of organizational decision-making in the digital era. This study aims to analyze the factors influencing successful AI adoption in MIS, evaluate its impact on strategic decision-making effectiveness, and explore the mediating role of dynamic capabilities. Grounded in the Technology Acceptance Model (TAM) and Dynamic Capabilities Theory, a conceptual framework was developed and tested using a mixed-methods approach. Quantitative data were collected from 715 respondents across six industry sectors in Indonesia, while qualitative insights were derived from case studies in 25 organizations with varying levels of AI implementation maturity. Results from Structural Equation Modeling revealed that perceived usefulness, ease of use, organizational readiness, and management support significantly influence AI adoption in MIS. The integration of AI was found to improve decision quality (34.7%), speed (42.3%), predictive accuracy (28.6%), strategic alignment (31.2%), and risk assessment capabilities (36.8%). Qualitative findings highlighted key implementation challenges, including data quality, skills gaps, employee resistance, and integration complexity. This study contributes theoretically by enriching TAM with organizational and strategic dimensions, and practically by offering a comprehensive framework to guide AI integration in MIS for sustained competitive advantage.
Co-Authors Al Khowarizmi Angkat, Fhatiya Alzahra Permatasari, Dhyta