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All Journal Jurnal Informasi dan Teknologi Jurnal Manajemen Sistem Informasi
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Universitas Tjut Nyak Dhien
Computer Science & IT Decision Sciences, Operations Research & Management

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Application of Artificial Intelligence in Medical Diagnostics: Applications and Implications in the Healthcare Sector Arnes Yuli Vandika; Dadang Muhammad Hasyim; Devi Rahmah Sope; Legito; Novycha Auliafendri
Jurnal Informasi dan Teknologi 2025, Vol. 7, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.vi0.674

Abstract

Artificial Intelligence (AI) has emerged as a transformative innovation in the medical diagnostic sector. This study explores the application and implications of AI in healthcare services at RSUD Dr. H. Abdul Moeloek, Bandar Lampung. Using a qualitative case study method, data were obtained through in-depth interviews and participatory observation. The results show that AI contributes significantly to improving diagnostic accuracy and speed, particularly in radiological imaging. However, limitations in technological infrastructure and system integration were found to hinder its optimal use. Furthermore, the readiness of human resources remains a critical factor. Although there is optimism among medical staff, a lack of technical training has led to gaps in understanding and utilization. Ethical and legal concerns also emerged, especially regarding responsibility in case of misdiagnosis and the protection of patient data. The absence of specific regulations and digital ethics protocols presents a major barrier to AI adoption. This research concludes that while the implementation of AI in medical diagnostics shows promising outcomes, it still faces institutional and regulatory challenges. Strengthening digital literacy among healthcare workers, developing standard operating procedures, and building a secure infrastructure are essential. Collaboration between hospitals, academic institutions, and government bodies is needed to create an inclusive and ethical AI-based healthcare ecosystem.
Rekonfigurasi Kinerja Sektor Publik melalui Literasi Data Strategis: Model Operasionalisasi Berbasis Kompetensi dalam Kerangka Data-Driven Governance Legito; Muhammad Dicky Syahputra Lubis; Nurul Afni
Jurnal Manajemen Sistem Informasi (JMASIF) Vol. 5 No. 1 (2026): April 2026
Publisher : Divisi Riset, Lembaga Mitra Solusi Teknologi Informasi (L-MSTI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59431/jmasif.v5i1.721

Abstract

Digital transformation has reshaped public sector governance toward data-based decision-making that is measurable, accountable, and outcome-oriented. Data functions as a central foundation in planning, policy formulation, and performance evaluation. Such transformation requires strengthening strategic data literacy as a core competency of public officials in identifying, understanding, utilizing, communicating, and ethically reflecting on data use. This study applies a quantitative approach with an explanatory research design and Partial Least Squares–Structural Equation Modeling (PLS-SEM) using a hierarchical component model. Strategic Data Literacy is modeled as a third-order construct formed by five formative dimensions, while Public Sector Performance is measured reflectively through indicators of efficiency, effectiveness, and service equity. Empirical results indicate a positive and significant effect of strategic data literacy on public sector performance (β = 0.61; p < 0.001), with an R² value of 0.54. Data utilization and data understanding emerge as dominant dimensions in strengthening organizational analytical capacity. Findings demonstrate that a competency-based operationalization model supports the reconfiguration of public sector performance within a structured data-driven governance framework.
Co-Authors Arnes Yuli Vandika Dadang Muhammad Hasyim Devi Rahmah Sope Muhammad Dicky Syahputra Lubis Novycha Auliafendri Nurul Afni