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All Journal Aptisi Transactions on Management International Transactions on Education Technology (ITEE)
Aprila Yusuf, Natasya
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Social Sciences

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Enhancing Security Frameworks with Artificial Intelligence in Cybersecurity Jonas, Dendy; Aprila Yusuf, Natasya; Rahmania Az Zahra, Achani
International Transactions on Education Technology (ITEE) Vol. 2 No. 1 (2023): International Transactions on Education Technology (ITEE)
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/itee.v2i1.428

Abstract

Cybersecurity, in the digital era we live in today, has become a major concern that demands innovation. Data Science and Artificial Intelligence (AI) have played a central role in changing the way we understand and address cyber threats. This research will review the important role of innovation in this technology in improving an organization's ability to detect, prevent, and respond to cyber attacks. Identifying patterns and gaining insights from security events in cyber data, while developing appropriate data-based models, is a key element in realizing automated and intelligent security systems. This research reviews needs in the cyber security domain that can be addressed through Artificial Intelligence (AI) techniques. In this study, we employed quantitative methods to assess the impact of artificial intelligence on enhancing cybersecurity by distributing questionnaires to 85 respondents, which included companies operating in the banking and IT sectors. In addition, this research will explore how data-based intelligent decision-making systems are able to protect systems from known and unknown cyber attacks. This research will conclude by considering the future potential of Artificial Intelligence and cybersecurity.
Exploring the Impact of Data Quality on Decision-Making Processes in Information Intensive Organizations Khong, Isaac; Aprila Yusuf, Natasya; Nuriman, Arbi; Bayu Yadila, Ahmad
APTISI Transactions on Management (ATM) Vol 7 No 3 (2023): ATM (APTISI Transactions on Management: September)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v7i3.2138

Abstract

This study investigates the influence of data quality on decision-making processes within organizations that heavily rely on information for their operations. With the increasing digitalization and proliferation of data in today's business landscape, the quality of data has emerged as a critical factor in ensuring accurate and effective decision-making. Through a comprehensive review of existing literature and an empirical analysis, this research aims to shed light on the relationship between data quality and decision-making outcomes. The study employs a mixed-methods approach, utilizing both qualitative interviews and quantitative surveys to gather insights from professionals across various information-intensive sectors. The findings reveal that data quality significantly impacts the accuracy, reliability, and timeliness of decisions made within these organizations. Moreover, the study identifies key challenges that organizations face in maintaining data quality and suggests potential strategies to enhance decision-making processes. The results of this research contribute to a deeper understanding of the pivotal role data quality plays in the success of information-intensive organizations and provide practical implications for managers and decision-makers.
Unlocking Organizational Potential: Assessing the Impact of Technology through SmartPLS in Advancing Management Excellence Aaron Beldiq, Eiser; Callula, Brigitta; Aprila Yusuf, Natasya; Rahmania Az Zahra, Achani
APTISI Transactions on Management (ATM) Vol 8 No 1 (2024): ATM (APTISI Transactions on Management: January)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v8i1.2195

Abstract

This study aims to explore the organizational potential in facing the impact of implementing Business Intelligence System (BIS) technology using Partial Least Squares Structural Equation Modeling (SmartPLS) as the analytical tool. We conducted research on several organizations that have adopted Business Intelligence (BIS) with the goal of enhancing managerial excellence. Data collection was carried out online, involving 150 respondents from 5 organizations in Indonesia, the majority of whom are already familiar with and have implemented BIS technology in their organizations. We evaluated the impact of this technology, particularly on organizational performance, decision-making processes, and business process optimization. This research not only synthesizes knowledge from relevant literature but also provides a holistic understanding of the impact of Business Intelligence System (BIS) technology, specifically through its success within an organizational context. The findings of this research are expected to offer a profound insight into how the adoption of BIS can transform organizational paradigms in managing information, deciding strategies, and improving operational efficiency.
Co-Authors Aaron Beldiq, Eiser Bayu Yadila, Ahmad Callula, Brigitta Jonas, Dendy Khong, Isaac Nuriman, Arbi Rahmania Az Zahra, Achani