PENGUKURAN EFISIENSI BANK PERKREDITAN RAKYAT SYARIAH DI INDONESIA MENGGUNAKAN METODE DATA ENVELOPMENT ANALYSIS (DEA) DENGAN PENDEKATAN INTERMEDIASI TAHUN 2025
DOI:
https://doi.org/10.61722/jiem.v4i6.11001Keywords:
Islamic Rural Banks, Efficiency, Data Envelopment Analysis, Intermediation Approach, Islamic Banking.Abstract
Islamic Rural Banks (BPRS) play an important role in supporting the development of the Islamic financial industry through their intermediation function of collecting public funds and channeling them into financing activities. As competition in the Islamic banking sector continues to increase, efficiency has become an essential indicator for evaluating the ability of BPRS to utilize available resources optimally. This study aims to measure the efficiency level of Islamic Rural Banks in Indonesia in 2025 using the Data Envelopment Analysis (DEA) method with an intermediation approach. This research employs a quantitative method using secondary data obtained from the Islamic Banking Statistics published by the Financial Services Authority (OJK) in 2025. The units of analysis consist of 22 provinces with active BPRS operations. The input variables include total assets and Third-Party Funds (TPF), while financing is used as the output variable. The analysis applies the DEA CCR model (Constant Return to Scale) with an input-oriented approach. The results reveal that the efficiency performance of BPRS varies across provinces. Of the 22 provinces analyzed, only three provinces, namely Riau Islands, Lampung, and DKI Jakarta, achieved full efficiency with a DEA score of 1.000. Meanwhile, the remaining 19 provinces were found to be below the efficiency frontier, indicating opportunities to improve performance through a more optimal utilization of assets and third-party funds in generating financing. The findings suggest that the effectiveness of the intermediation function plays a more significant role than the size of resources owned in determining the efficiency level of Islamic Rural Banks in Indonesia.
References
Abidin, Z., & Endri. (2009). Kinerja efisiensi teknis bank pembangunan daerah: Pendekatan Data Envelopment Analysis (DEA). Jurnal Akuntansi dan Keuangan, 11(1), 21–29.
Ascarya, & Yumanita, D. (2008). Comparing the efficiency of Islamic banks in Indonesia and Malaysia using Data Envelopment Analysis. Bulletin of Monetary Economics and Banking, 11(2), 95–119.
Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in Data Envelopment Analysis. Management Science, 30(9), 1078–1092. https://doi.org/10.1287/mnsc.30.9.1078
Berger, A. N., & Humphrey, D. B. (1997). Efficiency of financial institutions: International survey and directions for future research. European Journal of Operational Research, 98(2), 175–212. https://doi.org/10.1016/S0377-2217(96)00342-6
Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429–444. https://doi.org/10.1016/0377-2217(78)90138-8
Coelli, T. J., Rao, D. S. P., O'Donnell, C. J., & Battese, G. E. (2005). An introduction to efficiency and productivity analysis (2nd ed.). Springer. https://doi.org/10.1007/b136381
Cooper, W. W., Seiford, L. M., & Tone, K. (2007). Data Envelopment Analysis: A comprehensive text with models, applications, references and DEA-Solver software (2nd ed.). Springer. https://doi.org/10.1007/978-0-387-45283-8
Fare, R., Grosskopf, S., & Lovell, C. A. K. (1994). Production frontiers. Cambridge University Press. https://doi.org/10.1017/CBO9780511551710
Fadhlul Mubarak, Aslanargun, A., & Sıklar, İ. (2021). High order spatial weighting matrix using Google Trends. International Journal of Research and Review, 8(11), 388–396. https://doi.org/10.52403/ijrr.20211150
Fadhlul Mubarak, Aslanargun, A., & Sıklar, İ. (2022). GSTARIMA model with missing value for forecasting gold price. Indonesian Journal of Statistics and Its Applications, 6(1), 90–100. https://doi.org/10.29244/ijsa.v6i1.90-100
Fadhlul Mubarak, Mardhotillah, B., Sundara, V. Y., Germansah, & Jiblathar, P. (2026). Pengelompokan provinsi berdasarkan dinamika nasabah-debitur BPR Syariah menggunakan metode clustering. EKOMA: Jurnal Ekonomi, Manajemen, Akuntansi, 5(3), 3082–3092. https://doi.org/10.56799/ekoma.v5i3.14569
Hadad, M. D., Hall, M. J. B., Kenjegalieva, K., Santoso, W., & Simper, R. (2011). Banking efficiency and stock market performance: Evidence from Indonesia. Applied Financial Economics, 21(16), 1141–1154. https://doi.org/10.1080/09603107.2011.561196
Ismail, F., Majid, M. S. A., & Rahim, R. A. (2013). Efficiency of Islamic and conventional banks in Malaysia. Journal of Financial Reporting and Accounting, 11(1), 92–107. https://doi.org/10.1108/JFRA-03-2013-0011
Kamarudin, F., Sufian, F., & Nassir, A. M. (2016). Does country governance foster revenue efficiency of Islamic and conventional banks in GCC countries? EuroMed Journal of Business, 11(2), 181–211. https://doi.org/10.1108/EMJB-06-2015-0026
Muallimah, L., & Haq, F. (2024). The use of Data Envelopment Analysis (DEA) method in measuring the efficiency of Sharia Rural Banks in D.I. Yogyakarta. Journal of Islamic Economic Scholar, 5(1), 116–136. https://doi.org/10.14421/jies.2024.5.1.116-136
Otoritas Jasa Keuangan. (2025). Statistik Perbankan Syariah Tahun 2025. Jakarta: OJK.
Pebrianti, I. Y. (2021). Analisis tingkat efisiensi Bank Pembiayaan Rakyat Syariah (BPRS) di Jawa Barat menggunakan metode Data Envelopment Analysis. Journal of Applied Islamic Economics and Finance, 1(2), 424–434. https://doi.org/10.35313/jaief.v1i2.2475
Rosman, R., Wahab, N. A., & Zainol, Z. (2014). Efficiency of Islamic banks during the financial crisis. Journal of Islamic Accounting and Business Research, 5(1), 36–58. https://doi.org/10.1108/JIABR-01-2012-0004
Rusydiana, A. S. (2018). Efisiensi dan stabilitas bank umum syariah di Indonesia. Akuntabilitas: Jurnal Ilmu Akuntansi, 11(2), 203–222. https://doi.org/10.15408/akt.v11i2.7033
Septiani, E., & Rani, L. N. (2020). Analisis tingkat efisiensi Bank Pembiayaan Rakyat Syariah periode 2012–2018 menggunakan metode Data Envelopment Analysis. Jurnal Ekonomi Syariah Teori dan Terapan, 7(7), 1378–1390. https://doi.org/10.20473/vol7iss20207pp1378-1390
Sufian, F., & Noor, M. A. N. M. (2009). The determinants of Islamic banks’ efficiency changes. International Journal of Islamic and Middle Eastern Finance and Management, 2(2), 120–138. https://doi.org/10.1108/17538390910965149
Tone, K. (2001). A slacks-based measure of efficiency in Data Envelopment Analysis. European Journal of Operational Research, 130(3), 498–509. https://doi.org/10.1016/S0377-2217(99)00407-5
Wasiaturrahma, Sukmana, R., Ajija, S. R., Salama, S. C. U., & Hudaifah, A. (2020). Financial performance of rural banks in Indonesia: A two-stage DEA approach. Heliyon, 6(7), e04390. https://doi.org/10.1016/j.heliyon.2020.e04390
Yudistira, D. (2004). Efficiency in Islamic banking: An empirical analysis of eighteen banks. Islamic Economic Studies, 12(1), 1–19.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 JURNAL ILMIAH EKONOMI DAN MANAJEMEN

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.











