Article Per Year (5 Year)
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All Journal Infotech: Journal of Technology Information Jurnal Sisfotek Global
I Ketut Sudaryana
Universitas Budi Luhur
Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering

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Artificial Intelligence (AI) Ethics in Fintech and Startup Ecosystems: A Systematic Literature Review Analysis Aditya Rawasaputra; Rahmat Tullah; I Ketut Sudaryana; Jan Everhard Riworuhi
JURNAL SISFOTEK GLOBAL Vol 16, No 1 (2026): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v16i2.16229

Abstract

Artificial intelligence (AI) is reshaping the fintech and startup ecosystem, offering efficiency in credit scoring, fraud detection, investment personalization, and customer service. Yet, its adoption raises pressing ethical challenges, particularly in Indonesia and Southeast Asia. This study conducts a systematic literature review (SLR) using the PRISMA protocol, analyzing over 80 scholarly articles, industry reports, and regulatory documents to examine key ethical issues in AI-driven finance. Findings highlight concerns around algorithmic transparency, data bias, privacy protection, accountability in automated decision-making, and regulatory compliance. Case studies of Indonesian fintech firms reveal emerging best practices, including explainable AI, fairness audits, compliance with the Personal Data Protection Law (UU PDP), and ethics committees. Regulatory frameworks from OJK and international standards such as GDPR and the EU AI Act provide critical guidance, though implementation challenges persist. The review concludes that embedding ethics into AI development lifecycles, strengthening cross-sector collaboration, and enhancing digital literacy are essential to building an inclusive, transparent, and sustainable fintech ecosystem.
DAMPAK ADOPSI KECERDASAN BUATAN TERHADAP KINERJA USAHA MIKRO, KECIL, DAN MENENGAH (UMKM) Sucipto Basuki; Riyanto Riyanto; I Ketut Sudaryana; Jan Everhard Riwurohi
Infotech: Journal of Technology Information Vol 12, No 1 (2026): JUNI (In Progress)
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v12i1.593

Abstract

The advancement of Artificial Intelligence (AI) has significantly accelerated digital transformation across various sectors, particularly Micro, Small, and Medium Enterprises (MSMEs). This Research aims to investigate the effects of AI integration on the operational efficiency of MSMEs in the Cibitung District of Bekasi Regency. Empirical data were gathered through a survey of MSME stakeholders, using a meticulously structured questionnaire, and subsequently analyzed using data-driven methodologies within the Orange Data Mining application. The analytical process encompassed data preprocessing and correlation analysis. The results reveal a positive correlation between AI integration and MSME operational performance. A correlation coefficient of 0.726 indicates a robust positive association between AI adoption and MSME sales performance, whereas an R² of 52.7% indicates that the model exhibits moderate to good predictive capability in explaining variations in MSME performance. These findings suggest that adopting artificial intelligence can enhance operational efficiency, boost business productivity, and expand MSMEs’ market reach. This study enriches the existing literature by proposing an analytical framework grounded in Orange Data Mining as a viable alternative to conventional analytical methodologies in MSME Research, while simultaneously underscoring the practical implications for digital transformation strategies and policy formulation aimed at facilitating AI adoption within the MSME sector.
Co-Authors Aditya Rawasaputra Jan Everhard Riworuhi Rahmat Tullah Riyanto Riyanto Ruwirohi, Jan Everhard Sucipto Basuki