Designing Citizen Business Loan Model to Reduce Non-Performing Loan: An Agent-based Modeling and Simulation Approach in Regional Development

Moses L Singgih, Bambang Syairudin, Tatbita T. Suhariyanto


Citizen Business Loan (CBL) constitutes a program poverty alleviation based on economic empowerment of small and medium enterprise. This study focuses on implementation of CBL at Regional Development Bank branch X. The problem is the existing of interdependencies between CBL’s implements (Bank) and the uncertainty of debtor’s capability in returning the credit. The impact of this circumstance is non-performing loan (NPL) becomes relatively high (22%). The ultimate objective is to minimize NPL by designing the model based on the agent that can represent the problem through a simulation using agent-based modeling and simulation (ABMS). The model is considered by managing the probability of the debtor to pay or not based on 5 C categories, they are: character, capacity, capital, condition, and collateral that inherent to each debtor. There are two improvement scenarios proposed in this model. The first scenario only involves the first category of debtor in simulation. The result of this scenario is NPL value as 0%. The second scenario includes the first and second of debtor’s category in simulation and resulting NPL value between 4.6% and 11.4%.


Citizen Business loan (CBL); Non-Performing Loan; Agent-based Modeling; and Simulation

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Bank Indonesia, (2004). Peraturan Bank Indonesia Nomor 6/9/PBI/2004 tentang Tindak Lanjut Pengawasan dan Penetapan Status Bank.

Borshchev, A. & Filippov, A., (2004). From System Dynamics and Discrete Event to Practical Agent Based Modeling : Reasons, Techniques, Tools.

DeYoung, R., Glennon, D., & Nigro, P. (2008). Borrower–lender distance, credit scoring, and loan performance: Evidence from informational-opaque small business borrowers. Journal of Financial Intermediation, 17(1), 113-143.

Ismail. (2010). Akuntansi Bank. Jakarta : Penerbit Kencana.

Johnston, D., & Morduch, J. (2008). The unbanked: evidence from Indonesia. The World Bank Economic Review, 22(3), 517-537.

Komite Kredit Usaha Rakyat, (2013). Sebaran Penyaluran Kredit Usaha Rakyat Periode November 2007- Februari 2013. Available at: [Accessed March 28, 2013].

Macal, C.M. & North, M.J., (2009). Agent-Based Modeling And Simulation. In Proceedings of the 2009 Winter Simulation Conference. Argonne, United States of America, pp. 86–98.

Manove, M., Padilla, A. J., & Pagano, M. (2001). Collateral versus project screening: A model of lazy banks. Rand journal of economics, 726-744.

Rosengard, J. K., & Prasetyantoko, A. (2011). If the banks are doing so well, why can't I get a loan? Regulatory constraints to financial inclusion in Indonesia. Asian Economic Policy Review, 6(2), 273-296.

Slovin, M. B., & Sushka, M. E. (1983). A model of the commercial loan rate. The Journal of Finance, 38(5), 1583-1596.

Sukrianto, H., (2013). Banyak Kredit Macet, Bank Jatim Kurangi Penyaluran KUR., p.1. Available at: [Accessed March 28, 2013].

Syarif, T., (2011). Prospek dan Kendala KUR dalam Mendukung Perkuatan Permodalan UKMK, Bidang Pengkajian Sumberdaya dan UKMdan Koperasi, Kementrian Negara Koperasi dan UKM.

Zulverdi, D., Gunadi, I., & Pramono, B. (2007). Bank portfolio model and monetary policy in Indonesia. Journal of Asian Economics, 18(1), 158-174.



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