Main Article Content
Abstract
P2P lending, commonly called online lending, is a service provider institution that provides borrowing and lending services in rupiah currency through an electronic system. The growth of P2P lending has increased rapidly since the pandemic of COVID-19 and led to an increase in the number of borrowers. Meanwhile, crime has also increased as many people can’t repay their loans. The chain of P2P lending must be controlled to suppress the growth of the population of people with online loans. This study constructs two P2P lending models by modifying the Kermack-McKendrick Epidemic Model. The population is divided into three sub populations: potential individuals, borrowers, and payers. Optimal control is used to suppress the population growth of borrower individuals through socialization with potential individuals or people with work potential and providing payment assistance for borrowers. This study constructs several optimal control scenarios for the two P2P lending models. From the comparison of optimal control scenarios, the optimal control recommendations that can suppress the population growth of borrower is to provide socialization to people with work potential and payment assistance for the borrower population.
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References
- Abdullah, A., Analysis of Online Loan Knowledge in Muslim Communities in Surakarta, (Journal of Indonesian Sharia Economics, 2021), 9(2), pp. 110-111.
- Boyce, W. E., and DiPrima, R. C., Elementary Differential Equations and Boundary Value Problem 9th Edition, (John Wiley and Sons, 2009), pp. 513.
- Brauer, F., Castillo-Chavez, C., and Feng, Z., Mathematical Models in Epidemiology, (Springer-verlag, New York, 2019), 69, pp. 26–35.
- Budiyanti, E., Resolving Illegal Financial Technology Businesses, (Journal of Brief Info, 2019), 11(4), pp. 20.
- CNBC Indonesia (2022, December 17), Data on Indonesian who cannot Pay Online Loans. Retrieved April 21, 2023, from https://www.cnbcindonesia.com/tech/20221217130201-37-397750/ini-bukti-makin-banyak-warga-ri-gak-bayar-pinjol-cek-datanya.
- Financial Services Authority: Financial Services Authority Regulation Number: 77/POJK.01/2016 concerning Information Technology-Based Money Lending and Borrowing Services, (Financial Services Authority, 2016), pp. 1–29.
- Hale, J. K. and Kocak, H., Dynamic and Bifurcation, (Springer-verlag, New York, 1991).
- Lewis L., Frank, Draguna L. Vrabie, and Vassilis L.Syrmos, Optimal Control, (John Wiley and Sons, 2012), pp. 112–115, 143–145.
- Madubueze, C. E., Dachollom, S., and Onwubuya, I. O., Controlling the Spread of COVID-19: Optimal Control Analysis, (Computational and Mathematical Methods in Medicine, 2020), pp. 5–10.
- Santoso, W., Trinugroho, I., and Risfandy, T., What Determine Loan Rate and Default Status in Financial Technology Online Direct Lending? Evidence from Indonesia, (Emerging Markets Finance and Trade, 2020), 56(2), pp. 351–369
- Wahyuni, R. A. E., and Turisno, B. E.: Illegal Financial Technology Practices in the Form of Online Loans in Review of Business Ethics, (Journal of Indonesian Legal Development, 2019), 1(3), pp. 380–381.
- Wiggins, S., Introduction to Applied Nonlinear Dynamical System and Chaos, (Springer-verlag, New York, 1990).
- Wonglimpiyarat, J., Fintech Banking Industry: A Systemic Approach, (Foresight, 2017), 19(6), pp. 590–603.
References
Abdullah, A., Analysis of Online Loan Knowledge in Muslim Communities in Surakarta, (Journal of Indonesian Sharia Economics, 2021), 9(2), pp. 110-111.
Boyce, W. E., and DiPrima, R. C., Elementary Differential Equations and Boundary Value Problem 9th Edition, (John Wiley and Sons, 2009), pp. 513.
Brauer, F., Castillo-Chavez, C., and Feng, Z., Mathematical Models in Epidemiology, (Springer-verlag, New York, 2019), 69, pp. 26–35.
Budiyanti, E., Resolving Illegal Financial Technology Businesses, (Journal of Brief Info, 2019), 11(4), pp. 20.
CNBC Indonesia (2022, December 17), Data on Indonesian who cannot Pay Online Loans. Retrieved April 21, 2023, from https://www.cnbcindonesia.com/tech/20221217130201-37-397750/ini-bukti-makin-banyak-warga-ri-gak-bayar-pinjol-cek-datanya.
Financial Services Authority: Financial Services Authority Regulation Number: 77/POJK.01/2016 concerning Information Technology-Based Money Lending and Borrowing Services, (Financial Services Authority, 2016), pp. 1–29.
Hale, J. K. and Kocak, H., Dynamic and Bifurcation, (Springer-verlag, New York, 1991).
Lewis L., Frank, Draguna L. Vrabie, and Vassilis L.Syrmos, Optimal Control, (John Wiley and Sons, 2012), pp. 112–115, 143–145.
Madubueze, C. E., Dachollom, S., and Onwubuya, I. O., Controlling the Spread of COVID-19: Optimal Control Analysis, (Computational and Mathematical Methods in Medicine, 2020), pp. 5–10.
Santoso, W., Trinugroho, I., and Risfandy, T., What Determine Loan Rate and Default Status in Financial Technology Online Direct Lending? Evidence from Indonesia, (Emerging Markets Finance and Trade, 2020), 56(2), pp. 351–369
Wahyuni, R. A. E., and Turisno, B. E.: Illegal Financial Technology Practices in the Form of Online Loans in Review of Business Ethics, (Journal of Indonesian Legal Development, 2019), 1(3), pp. 380–381.
Wiggins, S., Introduction to Applied Nonlinear Dynamical System and Chaos, (Springer-verlag, New York, 1990).
Wonglimpiyarat, J., Fintech Banking Industry: A Systemic Approach, (Foresight, 2017), 19(6), pp. 590–603.