Peningkatan pemahaman masyarakat tentang perlindungan hukum dan dampak pinjaman online

Authors

  • Dwi Affrimetty Tiemora Universitas Negeri Jakarta
  • Annisa Rahmi Faisal Universitas Negeri Jakarta

DOI:

https://doi.org/10.21009/jimd.v24i1.48886

Keywords:

pemahaman masyarakat, perlindungan hukum, pinjaman online

Abstract

Tujuan penelitian untuk menjelaskan bagaimana peran pemahaman hukum dalam mencegah terjeratnya masyarakat kepada pinjaman ilegal berbasis online yang saat ini dengan mudah diakses melalui smartphone.Metode penelitian dilakukan dengan deskriptif kualitatif yang menggunakan data primer dan sekunder. Lokasi penelitian di Kampung Melayu, Jakarta. Hasil penelitian, pasar Fintech dalam bentuk pinjaman online dianggap cocok, bahkan penetrasi kepemilikan dan penggunaan telepon selularpun sangat tinggi meskipun masyarakat belum memiliki akses keuangan. Apalagi disaat kondisi ekonomi yang sulit dan ditambah dengan perilaku masyarakat digital yang konsumtif, membuat pinjaman online menjadi solusi terbaik bagi mereka tanpa memikirkan dampak jangka panjang yang timbul dikemudian hari, seperti gagal bayar karena bunga yang tinggi. Akibatnya, masih banyak masyarakat yang mengalami tindak kekerasan melalui media online dan media sosial (teror whatsapp, penyebaran data kepada kebarat, hingga teror melalui telepon dan pesan singkat). Oleh karena itu dibutuhkan pemahaman dan kesadaran hukum yang tinggi dari masyarakat agar dapat mengetahui dampak dan resiko dari penggunaan pinjaman online. Dengan upaya memberikan pemahaman hukum lewat kegiatan seminar kepada masyarakat di Kelurahan Kampung Melayu, Jakarta, diharapkan masyarakat menjadi sadar akan ketentuan hukum yang berlaku dan mengetahui upaya hukum yang dapat dilakukan ketika berhadapan dengan tindak kekerasan akibat Pinjol ilegal.

References

Ahelegbey, D., Giudici, P., & Pediroda, V. (2023). A network based fintech inclusion platform. Socio-Economic Planning Sciences, 87, 101555. https://doi.org/10.1016/j.seps.2023.101555

Alkhalili, M., Qutqut, M. H., & Almasalha, F. (2021). Investigation of Applying Machine Learning for Watch-List Filtering in Anti-Money Laundering. IEEE Access, 9, 18481–18496. https://doi.org/10.1109/access.2021.3052313

Allcott, H., Kim, J. J., Taubinsky, D., & Zinman, J. (2021). Are High-Interest Loans Predatory? Theory and Evidence from Payday Lending. SSRN Electronic Journal, 89(3). https://doi.org/10.2139/ssrn.3847544

Brown, E., & Piroska, D. (2021). Governing Fintech and Fintech as Governance: The Regulatory Sandbox, Riskwashing, and Disruptive Social Classification. New Political Economy, 27(1), 1–14. https://doi.org/10.1080/13563467.2021.1910645

Chang, W., Zhu, L., Wen, L., Song, J., Zou, Y., & Jin, Y. (2022). Effectiveness of seminar-case learning for use in practice teaching of statistics for undergraduates majoring in preventive medicine: a prospective cluster-randomized controlled trial. BMC Medical Education, 22(1). https://doi.org/10.1186/s12909-022-03297-8

El Hazzouri, M., El‐Bialy, R., Veresiu, E., & Main, K. J. (2023). Vulnerable consumer experiences of (dis)empowerment with consumer protection regulations. Journal of Consumer Affairs, 57(3). https://doi.org/10.1111/joca.12533

Hamarat, Ç., & Broby, D. (2022). Regulatory constraint and small business lending: do innovative peer-to-peer lenders have an advantage? Financial Innovation, 8(1). https://doi.org/10.1186/s40854-022-00377-y

Jianguo, D., Ali, K., Alnori, F., & Ullah, S. (2022). The nexus of financial development, technological innovation, institutional quality, and environmental quality: evidence from OECD economies. Environmental Science and Pollution Research, 29(38), 58179–58200. https://doi.org/10.1007/s11356-022-19763-1

Li, B., & Xu, Z. (2021). Insights into financial technology (FinTech): a bibliometric and visual study. Financial Innovation, 7(1). https://doi.org/10.1186/s40854-021-00285-7

Liu, C., YiDong, M., Xiao, Y., Zheng, W., & Hsu, C.-H. (2021). Finding the Next Interesting Loan for Investors on a Peer-to-Peer Lending Platform. IEEE Access, 9, 111293–111304. https://doi.org/10.1109/access.2021.3103510

Marjerison, R. K., Chae, C., & Li, S. (2021). Investor Activity in Chinese Financial Institutions: A Precursor to Economic Sustainability. Sustainability, 13(21), 12267. https://doi.org/10.3390/su132112267

Veit, D. J., & Thatcher, J. B. (2023). Digitalization as a problem or solution? Charting the path for research on sustainable information systems. Journal of Business Economics, 93(6). https://doi.org/10.1007/s11573-023-01143-x

Wang, C., Han, D., Liu, Q., & Luo, S. (2019). A Deep Learning Approach for Credit Scoring of Peer-to-Peer Lending Using Attention Mechanism LSTM. IEEE Access, 7, 2161–2168. https://doi.org/10.1109/access.2018.2887138

Wang, H., Kou, G., & Peng, Y. (2020). Multi-class misclassification cost matrix for credit ratings in peer-to-peer lending. Journal of the Operational Research Society, 72(4), 1–12. https://doi.org/10.1080/01605682.2019.1705193

Wulandari, E., Meuwissen, M. P. M., Karmana, M. H., & Lansink, A. G. J. M. O. (2021). The role of access to finance from different finance providers in production risks of horticulture in Indonesia. PLOS ONE, 16(9), e0257812. https://doi.org/10.1371/journal.pone.0257812

Xia, P., Ni, Z., Zhu, X., Zhang, J., & Jin, Y. (2020). A Novel Prediction Method Based on Improved Binary Glowworm Swarm Optimization and Multi-Fractal Dimension for P2P Lending Investment Risk. IEEE Access, 8, 23232–23245. https://doi.org/10.1109/access.2020.2970482

Downloads

Published

2024-10-30

How to Cite

Tiemora, D. A., & Faisal, A. R. (2024). Peningkatan pemahaman masyarakat tentang perlindungan hukum dan dampak pinjaman online. Jurnal Ilmiah Mimbar Demokrasi, 24(1), 438–444. https://doi.org/10.21009/jimd.v24i1.48886