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Journal of Management and Informatics
Published by Universitas Sains Dan Teknologi Komputer
ISSN : 29617731     EISSN : 29617472     DOI : 10.51903
Core Subject : Science,
Computer Science & IT Decision Sciences, Operations Research & Management
management and business economics involving operational management, management of human resources, finance management, marketing management, social and economic management
Arjuna Subject : Bisnis, Menejemen, dan Akutansi (semua kategori) - Sistem Informasi Menejemen
Articles 75 Documents
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Exploring the Role of Digital Tools in Ethical Managerial Decision-Making Álvarez, Miguel; Hassan, Leila
Journal of Management and Informatics Vol. 4 No. 3 (2025): December Season | JMI: Journal of Management and Informatics
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jmi.v4i3.306

Abstract

The rapid integration of digital technologies into managerial work reorganized ethical decision-making in organizations. Technology holds the promise of efficiency and transparency but leaves the impact of technology on moral thought and managerial accountability unclear. This research strives to analyze how digital technologies inform, enable, or complicate ethical managerial decision-making. Utilizing a qualitative exploratory research methodology, the research weaves evidence from an in-depth literature review and semi-structured interviews on Ethical Decision-Making Theory and Socio-Technical Systems Theory. Thematic coding suggests that online resources can enhance ethical consistency and moral awareness if used reflectively but reduce moral sensitivity based on reliance on algorithmic rationality. The findings suggest dynamic interplay between human judgment and computer mediation and underscore the merits of socio-technical integration under balance. A conceptual model for co-evolution modeling of digital intelligence and moral cognition in managerial contexts is proposed. Ethical decision-making in the digital era, this study argues, is less a question of algorithmic transparency and more a question of applying responsible human judgment in technologically mediated environments. The research makes a theoretical contribution by merging ethical thinking with socio-technical models of management and provides organisational practical advice on how to integrate moral thinking within digital environments of decision-making.
Implementation of Expert System Applications using Forward Chaining to Detect Dental Health Zahra , Zahra; Melyani, Melyani; Yusuf, Faif; Herawati, Metty Titin; Royanti, Suci; Rosihana, Athiy Dina
Journal of Management and Informatics Vol. 4 No. 3 (2025): December Season | JMI: Journal of Management and Informatics
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jmi.v4i3.212

Abstract

Dental diseases remain one of the most common health issues globally, often resulting from a lack of early detection and limited access to dental specialists. This research presents the implementation of an expert system that uses forward chaining to diagnose dental health conditions based on user-reported symptoms. The system integrates a knowledge base modeled from expert consultation with dentists, consisting of symptom sets and rule-based logic. Findings indicate that the Forward Chaining approach is effective for step-by-step rule evaluation and generates accurate diagnoses of diseases such as caries, gingivitis, periodontitis, halitosis, and pulpitis. The study demonstrates that expert systems can support preliminary dental screening and improve public awareness of dental health.
Value-Based Administration Services and Value-Based Care: Aligning Administrative Efficiency with Patient Outcomes Willie, Michael Mncedisi
Journal of Management and Informatics Vol. 4 No. 3 (2025): December Season | JMI: Journal of Management and Informatics
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jmi.v4i3.308

Abstract

Value-Based Care (VBC) is reshaping healthcare delivery by incentivising improved patient outcomes over service volume. However, its success is closely tied to the efficiency and responsiveness of administrative systems.This study introduces the concept of Value-Based Administration Services (VBAS) and explores how its integration with VBC can strengthen clinical performance, enhance operational efficiency, and support organisational sustainability. A qualitative literature review was conducted to analyse peer-reviewed articles, policy documents, and case studies. Thematic analysis was used to identify patterns and construct a conceptual framework illustrating the interdependence of VBAS and VBC. Findings indicate that administrative functions such as claims processing, fraud detection, and performance-based contracting are essential to achieving VBC objectives. Misaligned or inefficient administrative processes can compromise patient care, while well-structured VBAS systems support transparency, regulatory compliance, and cost control. VBAS enables VBC, transforming administrative functions from transactional support roles into strategic mechanisms for delivering value. The proposed framework offers healthcare leaders a practical model for aligning administrative and clinical strategies to achieve high-quality, patient-centred, and financially sustainable care.
Enhancing Decision Quality and Transparency via Machine Learning-Based Goodwill Impairment Estimation in Banks Wibisono, Gunawan; Nikhlis, Neilin; Wicaksono, Yosep Aditya; Faradila, Silvia
Journal of Management and Informatics Vol. 4 No. 3 (2025): December Season | JMI: Journal of Management and Informatics
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jmi.v4i3.233

Abstract

Goodwill impairment assessment remains a judgment-intensive process in banking institutions, where managerial discretion, information asymmetry, and regulatory complexity often challenge the quality of decisions and transparency. While prior studies have widely applied machine learning to financial risk assessment and credit analytics, they have paid limited attention to its role in improving managerial accountability in goodwill impairment decisions. This study aims to address this gap by developing and evaluating a machine-learning–based estimation framework to enhance the quality of decisions and transparency in bank-level goodwill impairment assessments. Using simulation-based analysis on synthetic financial statements, the proposed framework evaluates the performance of impairment estimation using quantitative metrics that capture predictive accuracy, decision consistency, and traceability. The findings demonstrate that ML-assisted estimation can systematically improve decision quality while strengthening transparency and accountability compared to traditional judgment-driven approaches. Beyond technical performance, the results indicate that machine learning can function as a governance-supporting mechanism by enabling more traceable and internally auditable impairment decisions. The study contributes theoretically by operationalizing transparency and accountability as measurable decision outcomes in corporate finance, and practically by offering banks a simulation-based tool for internal evaluation that does not rely on field experiments or sensitive proprietary data. Overall, the research highlights the potential of ML-enabled decision support systems to enhance both the quality and governance of goodwill impairment practices in the banking sector.
Supporting Strategic Intuition for Product Feature Innovation in Early-Stage Fintech Payments Start-ups Handoko, Sri; Qosidah, Nanik
Journal of Management and Informatics Vol. 4 No. 3 (2025): December Season | JMI: Journal of Management and Informatics
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jmi.v4i3.234

Abstract

Early-stage fintech payments start-ups face high uncertainty, limited historical data, and compressed decision cycles, making product feature innovation both critical and fragile. Despite growing attention to AI-supported tools and data-driven strategies, little is known about how strategic intuition guides product decisions in these contexts. This study develops a conceptual and practice-based framework to explore how strategic intuition, supported by digital leadership and human–AI collaboration, shapes feature ideation, prototyping, and prioritization processes. Using simulated product decision scenarios and data dummy analysis, the research maps decision points across development stages and examines how teams integrate intuitive judgment with analytical cues. Findings reveal that strategic intuition functions as a central mechanism for aligning feature choices with strategic goals, enhancing coherence and adaptability under uncertainty. Digital leadership legitimizes intuitive decisions, fosters cross-functional collaboration, and creates a psychologically safe environment, while AI tools complement rather than replace human judgment. The study contributes theoretically by positioning strategic intuition as a core element of product feature innovation in early-stage ventures and by integrating cognitive, social, and technological mechanisms into a unified framework. In practice, the framework provides actionable guidance for start-up teams to improve decision quality and speed without relying on costly field experiments, offering insights for managers, incubators, and policymakers seeking to support innovation under constraints. Overall, the research underscores the value of structured intuition as a deliberate, analytically informed process that advances understanding of cognition-supported innovation in nascent digital ventures.

Page 8 of 8 | Total Record : 75

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