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All Journal Aptisi Transactions on Management International Transactions on Education Technology (ITEE)
Rahmania Az Zahra, Achani
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.
Enhancing Organizational Efficiency through the Integration of Artificial Intelligence in Management Information Systems Bhima, Bhima; Rahmania Az Zahra, Achani; Nurtino, Tio; Firli, M. Zaki
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.v7i3.2146

Abstract

This research delves into AI's role in enhancing Management Information Systems for organizational efficiency. It employs cross-sector case studies to showcase AI's potential in automating tasks, offering predictive insights from historical data, and bolstering decision-making. While AI promises substantial benefits, it also poses technical and ethical challenges during implementation. AI integration emerges as a game-changer, liberating organizations from mundane tasks through automation. Predictive analytics empowers firms to foresee trends, fostering a competitive edge in decision-making. Yet, obstacles include algorithm compatibility with existing systems and the demand for heightened technical proficiency. Ethical considerations loom large, demanding robust privacy and fairness guidelines in AI data usage. This research underscores the importance of employee AI training and multidisciplinary teams for tackling technical hurdles. Ethical principles should permeate AI development and utilization. The study recommends a three-fold strategy: First, prioritize employee AI training for seamless adoption. Second, establish cross-disciplinary teams to navigate technical complexities. Third, embed ethics in every AI facet to maintain trust. In conclusion, a holistic approach allows organizations to seamlessly integrate AI into Management Information Systems, yielding operational efficiencies, superior decision-making, and a competitive edge in a dynamic business landscape.
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.
Navigating the Challenges of Digital Transformation in Traditional Organization Maratis, Jerry; Ramadan, Ahmad; Rahmania Az Zahra, Achani; Ahsanitaqwim, Ridhuan; Bennet, Daniel
APTISI Transactions on Management (ATM) Vol 8 No 3 (2024): ATM (APTISI Transactions on Management: September)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v8i3.2349

Abstract

Digital transformation has become a critical strategy for traditional organiza- tions to maintain competitiveness in an increasingly technology-driven market. Technologies such as fintech, blockchain, artificial intelligence (AI), and cloud computing have significantly reshaped operational efficiency and customer en- gagement within these organizations. However, traditional organizations, characterized by their legacy systems and hierarchical structures, encounter various challenges in adopting these technologies. This study primarily aims to explore the key barriers that hinder digital transformation in traditional organizations and to propose effective strategies for overcoming these challenges. Utilizing a comprehensive literature review from 2018 to 2023, this research examines key studies on digital transformation in traditional business contexts. The find- ings reveal major challenges, including organizational inertia, skills gaps, de- pendency on outdated systems, and leadership deficiencies. To address these barriers, the study proposes strategies such as leadership development, work- force retraining, and investment in modern digital infrastructure. The results suggest that successful digital transformation requires a multifaceted approach, aligning technological adoption with organizational culture and sustainability goals. This research provides valuable insights for traditional organizations nav- igating the complexities of digital transformation.
Co-Authors Aaron Beldiq, Eiser Ahsanitaqwim, Ridhuan Aprila Yusuf, Natasya Bennet, Daniel Bhima, Bhima Callula, Brigitta Firli, M. Zaki Jonas, Dendy Maratis, Jerry Nurtino, Tio Ramadan, Ahmad