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All Journal JURISMA: Jurnal Riset Bisnis & Manajemen JIKA: Jurnal Ilmu Keuangan dan Perbankan
Arjuna Rizaldi
Universitas Komputer Indonesia/University of Dubrovnik
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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Analisis Sistematis tentang Bagaimana Analisis Big Data Mempengaruhi Pengambilan Keputusan Bisnis dalam Sistem Informasi Manajemen Muhammad Iffan; Muhamad Nur Ramadhan; Arjuna Rizaldi
JURISMA : Jurnal Riset Bisnis & Manajemen Vol. 16 No. 1: April 2026
Publisher : Program Studi Manajemen, Fakultas Ekonomi dan Bisnis, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jurisma.v16i1.19514

Abstract

This study examines how can Big Data Analytics contributes to better business decision-making through the use of Management Information Systems. This research is driven by the urgent need for organizations to make faster and more accurate decisions amidst intense competition as traditional information systems are no longer able to handle large and complex data. This study adopted a literature observation method compiled with PRISMA guidelines which analyzed a total of 20 scientific articles to investigate the latest research that discusses the relationship between analytical capabilities and systems in supporting management processes. The results show that the collaboration between Big Data Analytics and MIS can help companies understand market changes, assess operational efficiency, and formulate strategies based on real-time information. However, issues related to data accuracy, system readiness, and a shortage of skilled personnel remain major obstacles in this research. This study is recommended to understand how the use of analytics in Management Information Systems (MIS) can improve decision-making quality and organizational performance, while emphasizing the importance of balancing technology, human capabilities, and managerial practices. Keywords: Big Data Analytics; Management Information Systems; Decision Making; Business Intelligence; Systematic Literature Review
MEMANFAATKAN BIG DATA DAN SISTEM INFORMASI MANAJEMEN UNTUK KELINCAHAN STRATEGIS: TREN DAN TANTANGAN DALAM EKONOMI DIGITAL Mayar Mohammed Sabah Ali Alkaabi; Arjuna Rizaldi; Dina Novianty
JURISMA : Jurnal Riset Bisnis & Manajemen Vol. 16 No. 1: April 2026
Publisher : Program Studi Manajemen, Fakultas Ekonomi dan Bisnis, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jurisma.v16i1.19519

Abstract

The digital economy has changed the way businesses understand and manage risk, and this has made the combination of Big Data Analytics (BDA) and Management Information System (MIS) fundamental to any organization. This research focuses on how the combination of BDA and MIS facilitates strategic agility in digitally led companies. This research utilizes the PRISMA framework in conducting a systematic literature review of 20 peer-reviewed articles between 2020 and 2025 sourced from Google Scholar. The research shows that while MIS integrates data within organizational frameworks, structures, and governance, data analytics increases the organization’s strategic sensing and forecasting interpretive abilities. While Strategic agility has been identified within the literature as a mediating capability explaining the relationship between the adoption of digital technologies and the improvement of organizational outcomes, and not as a direct result of its adoption, the literature does present a paradox, characterized by complex data governance, skill gaps, limited interoperability, and excessive analytical dependence that may narrow scope for managerial discretion. Keywords: Big Data Analytics, Digital Economy, Management Information Systems, Strategic Agility, Systematic Literature Review
Big Data Analysis in Management Information Systems for Financial Decision Making: A Systematic Literature Review Trisa Afrilia Friyadi; Arjuna Rizaldi; Agus Riyanto; Mayar Mohammed Sabah Ali Alkaabi
Jurnal Ilmu Keuangan dan Perbankan (JIKA) Vol. 15 No. 1: Desember 2025
Publisher : Program Studi Keuangan & Perbankan, Fakultas Ekonomi dan Bisnis, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jika.v15i1.19521

Abstract

The integration of Big Data Analysis into Management Information Systems (MIS) has become increasingly important in supporting financial decision-making in today’s data-driven business environment. As the volume and variety of financial data continue to grow, MIS is no longer limited to traditional reporting functions but must evolve into analytical systems that provide timely and accurate information for managerial decisions. This study explores how Big Data Analytics is integrated into MIS and examines its role in improving the quality and accuracy of financial decision-making through a Systematic Literature Review (SLR) based on the PRISMA guidelines. Peer-reviewed journal articles published between 2020 and 2025 were reviewed to identify research trends, main findings, and research gaps. The findings show that Big Data Analytics enhances MIS by improving information quality, speeding up data processing, and enabling the integration of data from multiple sources, which supports more effective financial decisions. However, most existing studies still focus mainly on the technical implementation of Big Data, while the managerial integration of Big Data within the MIS framework remains limited. Therefore, this study emphasizes the importance of an integrated approach that views Big Data as a strategic element of MIS, providing a conceptual basis for developing more effective Big Data–driven financial decision-making systems and offering directions for future research related to data governance and system design. Keywords: Big Data; Management Information Systems; Financial Decision Making; SLR; Digital Transformation
Co-Authors Agus Riyanto Dina Novianty Mayar Mohammed Sabah Ali Alkaabi Mayar Mohammed Sabah Ali Alkaabi Muhamad Nur Ramadhan Muhammad Iffan Trisa Afrilia Friyadi