Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : The Eastasouth Journal of Information System and Computer Science

The Role of Federated Learning in Enhancing Data Privacy in Distributed Environments in Indonesia ZM, Ajub Ajulian; Sinuraya, Enda Wista; Winardi, Bambang
The Eastasouth Journal of Information System and Computer Science Vol. 3 No. 01 (2025): The Eastasouth Journal of Information System and Computer Science (ESISCS)
Publisher : Eastasouth Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/esiscs.v3i01.720

Abstract

This study investigates the role of federated learning (FL) in enhancing data privacy within distributed environments in Indonesia. With the increasing reliance on digital technologies, data privacy has become a critical concern, particularly in decentralized systems. A quantitative research approach was employed, involving 130 respondents from various professional backgrounds engaged with distributed data systems. Data were collected using a structured questionnaire with a five-point Likert scale (1–5) and analyzed using SPSS version 25. Descriptive, correlation, and regression analyses revealed that federated learning significantly contributes to improving confidentiality, trust, and compliance in distributed environments. The results indicate that FL not only safeguards sensitive data but also enhances stakeholder confidence and supports adherence to regulatory standards, such as Indonesia’s UU PDP. The study provides empirical evidence supporting the adoption of federated learning as a privacy-preserving technology and offers practical insights for organizations and policymakers seeking secure and compliant digital ecosystems.
Analysis of the Trends in AI-as-a-Service (AIaaS) Implementation in Technology Companies in Indonesia Sinuraya, Enda Wista; ZM, Ajub Ajulian; Winardi, Bambang
The Eastasouth Journal of Information System and Computer Science Vol. 3 No. 01 (2025): The Eastasouth Journal of Information System and Computer Science (ESISCS)
Publisher : Eastasouth Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/esiscs.v3i01.721

Abstract

This study examines the impact of adoption drivers, perceived benefits, and implementation challenges of Artificial Intelligence-as-a-Service (AIaaS) on the organizational performance of technology companies in Indonesia. Using a quantitative approach, data were collected from 200 respondents through structured questionnaires and analyzed with multiple regression techniques. The results reveal that adoption drivers and perceived benefits have a significant positive influence on organizational performance, while implementation challenges exert a negative impact. These findings suggest that while AIaaS offers considerable potential for efficiency, innovation, and competitive advantage, unresolved barriers such as data security, system integration, and limited human resources hinder its effectiveness. This study contributes to the growing body of literature on AI adoption in emerging economies by highlighting the dual role of enablers and inhibitors in shaping AIaaS outcomes. Practical implications include the need for organizations to invest in digital skills development and risk management, and for policymakers to establish clear regulatory frameworks to accelerate responsible AIaaS adoption in Indonesia.