Rafi Rasidin
Universitas Kebangsaan Republik Indonesia, Bandung, Indonesia

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The Development of Artificial Intelligence Technology and Cyber Security Threats Siti Sa’adah; Yulianah Yulianah; Neysha Putri Vaquitasari; Eka Septiana; Rafi Rasidin; Wanda Laksniyunita
Advances in Community Services Research Vol. 4 No. 2 (2026): March - August
Publisher : Yayasan Pendidikan Bukhari Dwi Muslim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60079/acsr.v4i2.877

Abstract

Purpose: This study aims to examine the relationship between advances in Artificial Intelligence (AI) and the evolving cybersecurity landscape by identifying emerging AI-enabled threats, exploring AI-based defense mechanisms, and analyzing the challenges of implementing AI-driven cybersecurity systems. Research Method: A structured literature review using a qualitative descriptive approach was conducted. Relevant studies published between 2021 and 2025 were systematically identified through major academic databases using predefined search keywords. The selected studies were screened using inclusion and exclusion criteria and analyzed through thematic content analysis. Results and Discussion: The findings indicate that AI simultaneously functions as a catalyst for increasingly sophisticated cyber threats and as an enabler of advanced cybersecurity defenses. Three dominant themes emerged: the evolution of AI-driven threats, the application of AI in cybersecurity defense, and the technical and organizational challenges associated with AI implementation. Implications: The study highlights the importance of integrating technological innovation, human oversight, and governance frameworks to strengthen cybersecurity resilience. Originality: This review provides a holistic perspective by simultaneously examining AI-enabled threats, defensive applications, and implementation challenges within cybersecurity ecosystems.
Optimizing Raw Material Inventory Costs at the Corporate Macro Level: A Financial EOQ Approach and Risk Mitigation at PT. Mayora Indah Tbk (2024–2025) Rafi Rasidin; Asri Sundari; Garneta Dinarsuci; Shahnawaaz Kiara Amanda; Suci Fitrianti
Advances in Managerial Auditing Research Vol. 4 No. 3 (2026): June - September
Publisher : Yayasan Pendidikan Bukhari Dwi Muslim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60079/amar.v4i3.945

Abstract

Purpose: This study evaluates the adequacy of public data for applying Economic Order Quantity (EOQ), Safety Stock (SS), and Reorder Point (ROP) to PT Mayora Indah Tbk’s inventory for the 2024–2025 period. Research Method: This study employs a descriptive quantitative approach with a documentary design. The data were drawn from consolidated financial statements and sustainability reports, and were then evaluated based on physical data requirements, relevant costs, demand, and lead time. Results and Discussion: The public report provides only aggregate inventory values and does not disclose quantities, ordering costs, storage costs, or lead times for each material. The insurance coverage amount is not the annual premium, and data do not support the ordering frequency and previous SS parameters. Therefore, the estimates for EOQ, ROP, cost savings, and margin improvement cannot be validated. Implications: Applying the model requires transaction data at the homogeneous material level, including physical usage, incremental costs, order history, lead times, and service targets. The research findings serve as the basis for improving inventory data management and for subsequent implementation studies. Originality: This study highlights the methodological limitations of using consolidated financial statements to make operational EOQ decisions at large-scale FMCG companies.