Financial Literacy-Based Islamic Education and Deep Learning to Prevent Online Debt in Indonesian Students

  • Marzuki A
  • Mashuri M
  • . S
  • et al.
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Abstract

Online lending (pinjol) among Indonesian youth poses ethical and financial risks, particularly regarding riba in debt transactions. According to the Financial Services Authority (OJK), as of February 2025, individuals aged 19–34 held an outstanding balance of IDR 38.18 trillion, while non-performing loans for those under 19 reached IDR 3.6 billion. This study developed a Grade VIII Islamic Religious Education (PAI) textbook, Chapter 9: “Becoming a Trustworthy Person and Avoiding Riba in Trade and Debt Transactions”, integrating financial literacy with a deep learning approach. Using the ADDIE-based Research and Development (R&D) method, the textbook underwent needs analysis, design, expert validation, pilot testing, and evaluation. Expert reviews rated it “excellent” across content (91.4%), instructional design (89.7%), and contextual relevance (90.2%). Implementation with 62 students increased average scores from 65.3 to 84.7 (N-gain = 0.63), improving riba comprehension, critical thinking, and ethical decision-making, while reducing interest in online loans. These improvements were facilitated through the principles of Mindful Learning, which encouraged reflective awareness of the ethical implications of debt; Meaningful Learning, which connected Islamic financial values with real-life cases of digital lending; and Joyful Learning, which engaged students through interactive, problem-based, and collaborative tasks. The results underscore the potential of integrating financial literacy into Islamic education through deep learning pedagogy as a proactive means of fostering ethical financial behavior among adolescents.

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APA

Marzuki, A., Mashuri, M. M., . S., & Ilmi, N. (2025). Financial Literacy-Based Islamic Education and Deep Learning to Prevent Online Debt in Indonesian Students. Journal of Innovation and Technology, 2025(2). https://doi.org/10.61453/joit.v2025no16

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