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All Journal Jurnal Impresi Indonesia International Journal of Multidisciplinary Research of Higher Education (IJMURHICA) The Indonesian Journal of Computer Science
Nurcholis Ramlan
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Religion Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences

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Utilization of Artificial Intelligence in Government Hospital Information Systems: A Systematic Review Eva Hidayati, Isnina; Lusa, Sofian; Iriyanti, Iindra; Ramlan, Nurcholis; Indra Sensuse , Dana
Jurnal Impresi Indonesia Vol. 5 No. 2 (2026): Jurnal Impresi Indonesia
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/jii.v5i2.7588

Abstract

The use of Artificial Intelligence (AI) in healthcare continues to expand. Hospital Information Systems (HIS) play a crucial role in managing clinical and operational data within hospitals. With advancements in technology, the integration of AI into HIS is gaining increasing attention due to its potential to enhance efficiency, accuracy, and the overall quality of healthcare services. Currently, government hospitals face various challenges in delivering public health services, including lengthy administrative processes, limited medical personnel, and the growing need for faster, data-driven clinical decision-making. This study focuses on analyzing the role of AI in supporting HIS development in government hospitals, with the objective of improving efficiency, accuracy, and service quality. Using a Systematic Literature Review (SLR) approach, the study collects, evaluates, and analyzes recent literature on the application of AI within HIS in government hospitals, particularly in areas such as patient registration, diagnostic support, electronic medical record management, and digital triage systems. The expected outcome of this study is a more comprehensive understanding of how AI can improve hospital operational efficiency while enhancing the quality of patient experiences, especially within public healthcare contexts. In addition, the study identifies key challenges in implementing AI within HIS, including limited system interoperability, the need for stronger health data security and regulatory frameworks, and insufficient human resource readiness. Therefore, this research is expected to provide meaningful contributions to policymakers, system developers, and government hospitals in designing digital transformation strategies for public health services that are smarter, safer, and more patient-oriented.
Factors Influencing the Adoption of Multi Factor Authentication in the Public Sector: A Case Study of Indonesia National Single Window Agency Purnomo, Dencaswo; Ghaisani, Amanda; Sensuse, Dana Indra; Lusa, Sofian; Ramlan, Nurcholis; Indrawati, Nur
The Indonesian Journal of Computer Science Vol. 15 No. 2 (2026): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v15i2.5091

Abstract

This study aims to examine the factors that influence the intention and actual use of Multi-Factor Authentication (MFA) in the National Single Window Agency (LNSW). The research model integrates the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) with the addition of the Perceived Security (PS) construct. Data were collected from employees and vendor teams at the LNSW and analyzed using the Partial Least Squares Structural Equation Modeling (PLS-SEM) method. The results show that Perceived Ease of Use (PEOU) and Social Influence (SI) have a positive and significant effect on Behavioral Intention (BI). In addition, Perceived Security (PS) does not have a direct effect on Behavioral Intention, but it has a significant positive effect on Perceived Usefulness (PU). Other findings show that Behavioral Intention (BI) is a strong predictor of Actual Usage (AU) of MFA. These results confirm the relevance of the TAM and UTAUT models in explaining the adoption of security technology in the public sector, and emphasize the importance of ease of use and organizational influence in encouraging the adoption of MFA
Strengthening Security Awareness in the Era of Artificial Intelligence-Based Cyber Threats Patria, Nusandika; Amir, Sopian; Sensuse, Dana Indra; Lusa, Sofian; Indrawati, Nur; Ramlan, Nurcholis
International Journal of Multidisciplinary Research of Higher Education Vol 9 No 2 (2026): (April) Theme Education, Religion Studies, Social Sciences, STEM and Economic Dev
Publisher : Islamic Studies and Development Center in Collaboration With Students' Research Center Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Artificial intelligence (AI) is developing rapidly and is increasingly being applied in various fields, including cybersecurity. However, this development also introduces new, more sophisticated threats that are difficult to detect. AI-based cyber threats, including adaptive malware, highly personalized phishing, deepfakes for identity manipulation, adaptive distributed denial of service (DDoS) attacks, and automated ransomware, are projected to escalate by 2025. These threats' complexity requires a security approach that relies not only on technology but also on human awareness as the first line of defense. In Indonesia, the 2024 Cybersecurity Landscape Report, published by the National Cyber and Crypto Agency (BSSN), shows that public and institutional awareness of information security is still relatively low. This study presents a systematic literature review of 30 articles to examine how security awareness is being strengthened in the context of AI-based cyber threats. The review identified six main categories of AI enabled threats social engineering and phishing, content manipulation and impersonation, malware and ransomware, attacks against machine learning models, service disruption, and automated AI-orchestrated attacks. In parallel, seven categories of awareness strategies were synthesized: education and training programs, gamification and simulation-based learning, policy and governance support, technical and system-level controls, collaboration and multi-stakeholder engagement, legal and ethical frameworks, and psychological or human-centric approaches. The findings highlight that strengthening security awareness requires an integrated and multidimensional approach that bridges technological, organizational, regulatory, and human-centered efforts.
Co-Authors Amir, Sopian Dana Indra Sensuse Eva Hidayati, Isnina Ghaisani, Amanda Indra Sensuse , Dana Iriyanti, Iindra Lusa, Sofian Nur Indrawati, Nur Patria, Nusandika Purnomo, Dencaswo