Integration of Machine Learning in Financial Planning of Young Entrepreneurs in the Era of Digital Economy

Authors

  • Loso Judijanto IPOSS Jakarta, Indonesia
  • Farid Wahyudi Universitas Islam Raden Rahmat
  • Meiske Wenno Universitas Pattimura
  • Hasmia Melati Arifin Universitas Pattimura

DOI:

https://doi.org/10.58812/wsjee.v3i02.1893

Keywords:

Machine Learning, Financial Planning, Young Entrepreneurs, Digital Economy, Indonesia

Abstract

The integration of machine learning (ML) in financial planning offers transformative potential for young entrepreneurs navigating the dynamic digital economy in Indonesia. This study employs a qualitative approach, analyzing data from interviews with five informants, including entrepreneurs, financial advisors, and technology experts, to explore the benefits, challenges, and contextual factors influencing ML adoption. The findings highlight that ML enhances decision-making, improves efficiency, and provides personalized recommendations for financial planning. However, challenges such as limited technical expertise, high costs, cultural resistance, and the digital divide hinder widespread adoption. The study concludes that a multi-stakeholder approach involving government support, education, and infrastructure development is essential to bridge gaps and enable young entrepreneurs to leverage ML effectively. These insights contribute to understanding the interplay between technology and entrepreneurship, offering actionable recommendations for policymakers and practitioners.

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Published

2025-05-28

How to Cite

Integration of Machine Learning in Financial Planning of Young Entrepreneurs in the Era of Digital Economy (L. Judijanto, F. . Wahyudi, M. . Wenno, & H. M. . Arifin , Trans.). (2025). West Science Journal Economic and Entrepreneurship, 3(02), 194-200. https://doi.org/10.58812/wsjee.v3i02.1893