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All Journal Ranah Research : Journal of Multidisciplinary Research and Development JHSS (Journal of Humanities and Social Studies)
Nerissa Arviana
Universitas Indonesia, Depok, Indonesia
Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Economics, Econometrics & Finance Education Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Transportation Other

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AI-Driven Knowledge Sharing in the Banking Sector: Challenges and Approaches Nerissa Arviana; Afina Putri Dayanti; Dana Indra Sensuse; Sofian Lusa; Icha Mailinda; Novi Sofia Fitriasari
Ranah Research : Journal of Multidisciplinary Research and Development Vol. 8 No. 4 (2026): Ranah Research : Journal Of Multidisciplinary Research and Development
Publisher : Dinasti Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/rrj.v8i4.2121

Abstract

Digitalization is becoming increasingly relevant for banking, hence the necessity for a practical Knowledge Management (KM) system that can facilitate rapid innovation and ensure proper regulatory compliance. While there is growing recognition of KM as a strategic driver of performance, it is implemented in a fragmented way within financial institutions and limited by technology, organizational and governance barriers. This paper presents a Systematic Literature Review (SLR) following the PRISMA 2020 protocol, aiming to identify, evaluate and synthesize the academic literature published between 2020 and 2025 on the integration of AI and KM in the banking context. Forty primary studies were examined via narrative synthesis to address two research inquiries: the challenges of AI-driven knowledge sharing (RQ1) and AI-based methodologies and best practices that enhance knowledge management processes (RQ2). The findings identify three main challenge domains data and technology infrastructure, organizational and human factors, and governance, security, and ethics constraints and six main solution categories, including NLP, machine learning, knowledge graphs, expert systems, human-AI hybrid collaboration, and ethical AI governance frameworks. These findings lead to the idea that the use of AI improves the accessibility of knowledge, learning and creativity and its efficiency depends on the capacity of the appropriate KM, absorptive capacity and maturity of governance. The study offers a cohesive framework linking AI innovation to organizational knowledge performance within the finance sector.
User Perceptions Of The Security Of Personal Health Data On Chatgpt In Indonesia Kezia Amelia Putri; Nerissa Arviana; Camelia Fikrillah; Nenden C.S. Ningrum; Achmad Nizar Hidayanto
JHSS (JOURNAL OF HUMANITIES AND SOCIAL STUDIES) Vol. 10 No. 01 (2026): JHSS (Journal of Humanities and Social Studies) (SI)
Publisher : UNIVERSITAS PAKUAN

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Abstract

This study aims to explore the relationship between perceptions of data security and privacy, awareness of cyberattacks, and other factors that influence users’ trust in ChatGPT and their willingness to provide personal information. Data was collected via a questionnaire and analyzed using SmartPLS. This study examines eight main variables, namely: Privacy Concern (PC), Perceived Effectiveness of Government Regulation (PEGR), Trust in ChatGPT (TR), Moral Motive (MM), Perceived Intelligence (PI), Perceived Risk (PR), Perceived Benefit (PB), and Sharing Willingness (SW). This study tested nine hypotheses regarding the influence of these variables. Data were collected via a questionnaire using a 1–5 Likert scale and analyzed using SmartPLS to test the relationships among constructs using the Partial Least Squares Structural Equation Modeling (PLS-SEM) approach. The analysis results indicate that four of the proposed hypotheses were supported, with p-values < 0.05, suggesting that the decision to share personal data is significantly influenced by perceived benefits, which are in turn influenced by perceptions of ChatGPT’s intelligence and trust in the platform. Perceived Risk does not have a significant impact on Sharing Willingness; however, privacy concerns influence users’ perceptions of risk. The results of this study indicate that the benefits of using ChatGPT, significantly influences their willingness to share personal health data. This study suggests that the sample size should be increased to conduct a more in-depth analysis of information-sharing decisions.
Co-Authors Achmad Nizar Hidayanto Afina Putri Dayanti Camelia Fikrillah Dana Indra Sensuse Icha Mailinda Kezia Amelia Putri Nenden C.S. Ningrum Novi Sofia Fitriasari Sofian Lusa