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Data : Journal of Information Systems and Management
Published by PT Penerbit Ilmiah Indonesia
ISSN : -     EISSN : 30310008     DOI : https://doi.org/10.61978/data
Core Subject : Science,
Computer Science & IT Decision Sciences, Operations Research & Management
Data : Journal of Information Systems and Management with ISSN Number 3031-0008 (Online) published by Indonesian Scientific Publication, is a leading open-access and peer-reviewed scientific journal dedicated to publishing high-quality research in the field of information systems and management. Since its establishment, Data has been committed to advancing knowledge and understanding of the integration between information systems and management in a global context. The journal publishes research articles, technical papers, theoretical studies, and case studies that undergo rigorous peer review to ensure the highest standards of academic integrity and originality.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 43 Documents
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Overcoming Barriers to Decision Support Systems in Healthcare, Education, and Public Policy: Toward Inclusive and Ethical Implementation Subekti , Rino
Data : Journal of Information Systems and Management Vol. 3 No. 3 (2025): July 2025
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/data.v3i3.707

Abstract

Decision Support Systems (DSS) are increasingly recognized as vital tools for enhancing organizational decision-making across sectors. This narrative review synthesizes empirical evidence on the effectiveness, challenges, and strategic implications of DSS implementation, focusing on healthcare, education, supply chain, and public policy sectors. By examining these areas, the study highlights sector-specific dynamics and barriers to adoption. Using a systematic narrative approach, the study draws from literature indexed in Scopus, Google Scholar, and Web of Science, applying keyword-based searches and inclusion criteria to select peer-reviewed empirical and theoretical studies published within the last decade. The review finds, for example, that DSS in healthcare reduce sepsis-related mortality by enabling early detection, while in education, DSS support adaptive learning systems that align teaching with student performance data. In supply chains, DSS improve delivery times by up to 30%, and in public policy, they facilitate scenario-based analysis for transparent decision-making. However, systemic barriers such as infrastructure limitations, low digital literacy, and cultural resistance persist, especially in public sector adoption. These barriers impede the full realization of DSS potential and necessitate multi-level interventions. Integration of DSS has shown to not only optimize operational performance but also inform long-term strategic planning and policy development. The discussion underscores the importance of adaptive DSS models, user-centric design, and ethical governance in maximizing system effectiveness. The study concludes that while DSS offer transformative potential, their success depends on addressing institutional readiness and embedding ethical, inclusive frameworks. Future research should prioritize longitudinal studies on DSS adoption in healthcare and education, cross-country comparisons of supply chain DSS, and investigation into governance frameworks that ensure ethical use in public policy
A Narrative Review of the Integration of Big Data Analytics and Business Intelligence in Organizational Decision-Making Noviany , Henny
Data : Journal of Information Systems and Management Vol. 3 No. 4 (2025): October 2025
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/data.v3i4.710

Abstract

The integration of Big Data Analytics (BDA) and Business Intelligence (BI) has become increasingly vital for enhancing strategic decision-making within contemporary organizations. This narrative review aims to investigate how the convergence of BDA and BI influences decision-making processes, particularly in sectors such as finance, healthcare, manufacturing, and retail. The review employed comprehensive literature searches across Scopus, Web of Science, and Google Scholar using keyword combinations like “Big Data Analytics”, “Business Intelligence”, and “Decision Making”. Inclusion criteria prioritized peer-reviewed journal articles from the past decade. Findings reveal that BDA enables organizations to analyze large-scale data for hidden insights, while BI transforms these insights into visual and actionable intelligence. Together, they contribute to increased decision accuracy, cost reduction, and enhanced performance. Artificial Intelligence (AI), particularly machine learning and natural language processing, further amplifies these outcomes by enabling rapid and nuanced analysis of structured and unstructured data. However, systemic barriers persist, including fragmented data infrastructure, limited human capital, and concerns over data ethics and compliance. This review highlights the need for organizations to adopt a holistic, cross-functional approach to data integration while investing in digital skills development. It also underscores the importance of regional readiness and industry-specific strategies. The findings inform policymakers, practitioners, and scholars on the strategic imperatives for integrating BDA and BI to sustain innovation, responsiveness, and competitive advantage in the digital age
The Role of Systemic Enablers in Integrating Knowledge Management for Innovation Firmansyah, Boy
Data : Journal of Information Systems and Management Vol. 2 No. 1 (2024): January 2024
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/data.v2i1.717

Abstract

This narrative review explores the critical intersection between Knowledge Management (KM) practices and organizational innovation. As innovation becomes a key determinant of competitive advantage in the digital economy, organizations increasingly rely on KM strategies to harness collective expertise and accelerate problem-solving. The study synthesizes peer-reviewed literature drawn from Scopus, Web of Science, and Google Scholar using targeted keywords and Boolean combinations related to KM, innovation, and organizational learning. Inclusion criteria focused on empirical and theoretical studies that directly connect KM practices with innovation outcomes across diverse sectors and geographical settings. The results reveal that communities of practice, digital knowledge platforms, and strategic alignment of KM are primary drivers of innovation. Factors such as organizational culture, leadership style, and structural flexibility significantly mediate KM effectiveness. Cross-national comparisons highlight disparities in KM integration, with institutions in technologically advanced economies showing higher maturity levels. Challenges identified include resistance to change, underdeveloped digital infrastructure, and compartmentalized organizational silos. The discussion emphasizes policy and institutional strategies to overcome systemic constraints, including fostering leadership in KM and embedding KM within cross-functional collaboration initiatives. This review underscores the strategic importance of KM in enabling sustainable innovation and recommends future research on context-specific implementation and long-term impact. It calls for broader geographic representation and multi-sectoral analysis to develop more inclusive KM frameworks responsive to global innovation demands.
Beyond Technology: A Narrative Review of Organizational Dynamics in IT Change Management Noviany , Henny
Data : Journal of Information Systems and Management Vol. 2 No. 2 (2024): April 2024
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/data.v2i2.718

Abstract

This narrative review examines the organizational, technological, and human factors shaping IT-enabled change management (ITCM), with a particular focus on healthcare systems. The objective is to synthesize current evidence and highlight strategies that facilitate successful digital transformation across diverse contexts. A structured search was conducted in Scopus, Web of Science, PubMed, and Google Scholar, covering studies published between 2013 and 2023. Literature was selected based on relevance to ITCM, organizational readiness, stakeholder engagement, and implementation outcomes. A thematic analysis was applied to identify critical success factors and systemic challenges. Key findings indicate that adaptive organizational culture, strong leadership, and early stakeholder involvement are essential enablers of ITCM. Technological factors such as interoperability and system complexity remain major barriers, often compounded by user resistance. Human resource readiness—particularly digital literacy and training—emerges as a cornerstone of successful adoption. Comparative insights reveal that high-income countries benefit from robust infrastructure and governance, while low- and middle-income countries face persistent barriers related to limited resources and uneven capacity. The review concludes that ITCM requires integrated and context-sensitive strategies that combine technological innovation with organizational adaptability and human capital development. Practical implications include leadership training, cross-functional engagement, and targeted capacity building. Future research should employ longitudinal and system-dynamics approaches to assess sustainability and unintended consequences. This review contributes an integrative framework for understanding ITCM across organizational, technological, and socio-economic dimensions, offering insights for both policy and practice.
The Strategic Role of Information Systems in Advancing Sustainable Business Practices Puspitasari, Devi
Data : Journal of Information Systems and Management Vol. 2 No. 3 (2024): July 2024
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/data.v2i3.722

Abstract

Information systems are increasingly recognized as enablers of sustainable business practices. However, the extent of their impact across environmental, social, and governance (ESG) dimensions remains limited in current scholarship, particularly regarding mechanisms of influence. This narrative review investigates how information systems contribute to sustainability by enhancing operational efficiency, informing strategic decisions, and overcoming implementation challenges. Drawing from Scopus and Google Scholar, a systematic search was conducted using Boolean keyword combinations such as "Information Systems" AND "Sustainable Business Practices" and "Digital Transformation" AND "Sustainable Development." Studies meeting inclusion criteria—focused on the integration of IT in sustainability efforts—were synthesized thematically. The findings indicate that information systems significantly improve energy efficiency, reduce waste, and support environmental accounting. They enable real-time monitoring, predictive analytics, and decision-making frameworks grounded in ESG principles. Big data and cloud platforms are shown to facilitate cross-functional collaboration and innovation. However, implementation is often hindered by infrastructural limitations, high costs, and resistance to change, especially in developing regions. The role of regulatory support and organizational culture emerged as critical systemic enablers. Comparative insights between countries highlighted best practices that can be adapted to local contexts. This review concludes that information systems are not merely tools but strategic assets for sustainability. Policy incentives, capacity-building, and inclusive digital infrastructure are recommended to bridge implementation gaps. Future research should explore the integration of emerging technologies for enhanced impact. Promoting awareness and access remains essential to scaling sustainable practices globally.
The Strategic Role of AI in Enhancing MIS Performance and Innovation Setiawan, Adi Wahyu; Cahya, Waskita
Data : Journal of Information Systems and Management Vol. 2 No. 4 (2024): October 2024
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/data.v2i4.723

Abstract

The integration of Artificial Intelligence (AI) into Management Information Systems (MIS) has reshaped organizational operations across sectors. This narrative review explores the multidimensional impact of AI on MIS by synthesizing findings from recent peer-reviewed literature. The study aimed to analyze how AI technologies enhance MIS functions, focusing on areas such as process automation, decision support, HR management, corporate learning systems, and export-oriented quality control. Literature was sourced from databases like Scopus and Google Scholar using Boolean search techniques with targeted keywords. Inclusion criteria emphasized relevance, recency, and methodological rigor. Findings indicate that AI and Robotic Process Automation (RPA) optimize operational efficiency, while AI-enhanced decision-making tools offer strategic foresight across industries. In HRMIS, AI facilitates recruitment, performance appraisal, and diversity outcomes, whereas AI-driven learning platforms improve training efficiency and employee engagement. The implementation of AI in quality control and export readiness is linked to higher compliance, predictive analytics, and competitiveness. However, challenges such as algorithmic bias, data inconsistencies, and limited transparency underscore the need for systemic readiness. Theoretical frameworks including the TOE model and RBV elucidate how internal capabilities and environmental contexts shape AI integration. The study concludes that national policies, ethical design, infrastructure development, and cross-sector collaboration are essential for maximizing AI’s potential in MIS, paving the way for responsible and inclusive digital transformation.
Enhancing Enterprise Usability: Integrating Adaptive UI and Inclusive Design Strategies Purwandari, Nuraini; Dewi, Ratna Kusuma
Data : Journal of Information Systems and Management Vol. 3 No. 1 (2025): January 2025
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/data.v3i1.732

Abstract

In the last five years, there has been a significant shift in how user interface (UI) and user experience (UX) design are approached within enterprise systems, reflecting the growing demand for more intuitive, adaptive, and inclusive solutions. This study employs a narrative review based on 1,500 initial records screened from Scopus, IEEE Xplore, ACM Digital Library, and Google Scholar (2019–2024). After rigorous selection, 82 empirical studies were included, focusing on user-centered design (UCD), adaptive interfaces, and inclusive practices in enterprise environments.. The review draws upon academic sources indexed in Scopus, IEEE Xplore, ACM Digital Library, and Google Scholar. Keywords including "Enterprise Systems," "User Experience," "Interface Design," and "Adaptive User Interfaces" were utilized to identify relevant literature, with inclusion criteria focusing on empirical studies from the last decade. Findings from 82 included studies show that UCD practices enhance usability and user satisfaction, with some reporting 20–30% higher usability scores and faster task completion rates when end-users are actively involved throughout development.. Adaptive interfaces employing machine learning have demonstrated potential to increase task efficiency and user engagement by personalizing content and layout. Moreover, inclusive design strategies, such as universal accessibility features and assistive technologies, contribute to improved user experiences across ability levels. However, systemic barriers like organizational resistance and limited training still hinder optimal implementation. The review highlights the need for strategic design interventions, ongoing usability assessments, and context-sensitive adaptations. As enterprise systems continue to evolve, future research must explore long-term effects of adaptive design and develop unified frameworks for inclusive, responsive interfaces. These efforts are vital to ensure equitable access and effectiveness of enterprise technologies across global and cross-sectoral contexts.
Differentiated Impacts of Enterprise Information Systems on Financial Performance: A Meta Analytic Comparison of ERP, CRM, BI, and DSS Sugianto; Puspitasari2, Devi
Data : Journal of Information Systems and Management Vol. 3 No. 2 (2025): April 2025
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/data.v3i2.908

Abstract

 Enterprise Information Systems (EIS) including ERP, CRM, BI/BA, and DSS play critical roles in enhancing firm performance. However, their financial impacts vary across contexts, system types, and implementation designs. This study aims to systematically compare the financial effects of these systems using subgroup meta analysis, providing clarity on their differential contributions. A total of 120 studies were analyzed, focusing on three core financial outcomes: return on assets (ROA), return on sales (ROS), and revenue growth. Studies were selected from major IS meta analyses and empirical sources. Effect sizes were standardized using Fisher’s z, Hedges’ g, and log ratio transformations. A random effects model was applied, and subgroup analyses were conducted based on IS type and moderator variables including industry, region, firm size, and study design. CRM systems yielded the highest effect sizes (Cohen’s d = 0.67–0.75), especially in service sectors and developed markets. ERP systems showed moderate but consistent impact (d ≈ 0.54) through operational efficiency, while BI/BA (d ≈ 0.60) facilitated strategic planning. DSS contributed modestly (d ≈ 0.50). Moderator analysis revealed that larger firms and developed economies benefit more significantly from IS investments. Publication bias tests indicated some overestimation in cross sectional studies. These findings support the Resource Based View and complementary assets theory: IS value depends on integration with organizational capabilities. EIS types yield distinct financial benefits. CRM is optimal for rapid revenue and retention gains; ERP for internal efficiency; and BI for long term insights. Strategic alignment and contextual readiness determine ROI. The study offers theoretical and practical guidance for evidence based IS investment.
Strategic IT–Business Alignment and Big Data Analytics Capability: A Configurational Approach to Operational Excellence in Manufacturing Lukman
Data : Journal of Information Systems and Management Vol. 3 No. 3 (2025): July 2025
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/data.v3i3.909

Abstract

In the era of Industry 4.0, manufacturing firms face growing pressure to enhance operational performance through digital transformation. Central to this transformation is the strategic alignment between IT capabilities and business objectives, supported by advanced analytics and flexible IT infrastructures. This study investigates how different configurations of Strategic Alignment Maturity (SAMM), Big Data Analytics Capability (BDAC), IT flexibility, and business strategy types influence operational outcomes. Employing fuzzy set Qualitative Comparative Analysis (fsQCA) on data collected from 100 manufacturing firms, the research identifies multiple equifinal pathways to high operational performance, as measured by Overall Equipment Effectiveness (OEE) and SCOR metrics. Two dominant configurations emerge from the analysis. The first (R1) combines high levels of SAMM, IT flexibility, BDAC, and a Prospector strategy, highlighting a proactive, innovation oriented approach to operational excellence. The second configuration (R4) achieves similar performance through a different route leveraging BDAC, an Analyzer strategy, and strong CIO–business collaboration even in the absence of mature alignment structures. These results affirm that both alignment driven and analytics driven models can yield superior outcomes depending on organizational context and strategic orientation. The study contributes to the literature by demonstrating that high operational performance does not rely on a single universal model, but rather on the strategic orchestration of complementary capabilities. It also shows the effectiveness of fsQCA in uncovering complex causal relationships within organizational systems. Practically, the findings encourage manufacturing leaders to assess and tailor their alignment, analytics, and IT strategies according to their operational priorities and industry dynamics.
Operationalizing Responsible AI in Health Systems: Delphi Based Governance Metrics for Indonesia Puspitasari, Devi; Yuni T, Veronika
Data : Journal of Information Systems and Management Vol. 3 No. 4 (2025): October 2025
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/data.v3i4.910

Abstract

Artificial intelligence (AI) is rapidly transforming healthcare delivery in Indonesia. However, the responsible governance of AI systems especially in clinical settings remains underdeveloped. This study aims to identify and prioritize measurable governance indicators for AI in Indonesian healthcare through a Delphi based expert consensus process. A three round modified Delphi method was employed, engaging 30 interdisciplinary experts from healthcare, IT, cybersecurity, ethics, law, and patient advocacy. The process began with 40 indicators drawn from global frameworks (WHO, EU AI Act, ISO/IEC 42001, NIST RMF) and national references (UU PDP, SATUSEHAT). Experts rated each indicator on a 1–9 Likert scale across two iterative rounds. Consensus was defined as median ≥7 and IQR ≤1.5 using RAND/UCLA criteria.Out of 40 indicators, 24 achieved consensus. High priority indicators included clinical safety metrics (e.g., AUROC), data privacy compliance (PDP Law documentation), system integration (SATUSEHAT compatibility), and cybersecurity readiness (incident response plans). Transparency related indicators (e.g., training data summaries, model cards) failed to reach consensus, suggesting institutional gaps in AI explainability. The Delphi process underscored the importance of participatory governance, stakeholder trust, and contextual adaptation of international standards. Consensus indicators reflect domains where operational familiarity and regulatory anchors already exist, while non consensus areas highlight the need for capacity building and clearer guidelines. This study delivers a validated, measurable governance framework to guide responsible AI adoption in Indonesian healthcare. It supports policymaking, institutional audits, and procurement strategies aligned with both local regulation and global standards. Future work should pilot these indicators and expand their use in health system assessments and continuous governance improvement.

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