Main Article Content
Abstract
Purpose — Islamic banks in Nusa Tenggara Barat (NTB) province have experienced positive developments in assets, branches, and financing. This study aims to measure the resilience of Islamic banking in NTB using a composite bank variable and to determine how effectively the institution manages and absorbs various risks.
Method — The data used consisted of monthly data from 2010 to 2023, covering several banking variables, including the Financing to Deposits Ratio (FDR), Non-Performing Financing (NPF), Bank Size (BS), and Third-Party Fund (TPF). The analysis method employed in this study was the early warning system (EWS), utilising a non-parametric signal extraction approach.
Findings — All selected banking variables are used to measure the resilience of Islamic banking in NTB through the composite index of bank (CIB). The signal extraction method provides optimal thresholds for each selected banking variable and for the composite index (CIB). Visualisation results show the interval values that can absorb risk and maintain the resilience of Islamic banking as follows: (1) FDR between 81% and 102%; (2) NPF between 1.29% and 1.89%; (3) BS between 3.79% and 4.59%; (4) TPF between 4.16% and 4.58%; and (5) CIB between 10.66 and 28.14.
Implications — Assessing the resilience of Islamic banking in NTB involves identifying key banking variables to pinpoint sources of risk exposure, determining the optimal time horizon for policy interventions, and setting appropriate thresholds for the surveillance mechanism.
Originality — Currently, the resilience of Islamic banks at the provincial level has not been widely studied, particularly in NTB Province, where there has been a notable increase in Islamic banking offices and assets.
Keywords
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Copyright (c) 2025 Dimas Bagus Wiranatakusuma, Anggi Aprizal

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References
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References
Ahmad, S., Ahmad, W. M. W., & Shaharuddin, S. S. (2022). Is an excess of everything bad? Ramifications of excess liquidity on bank stability: Evidence from the dual banking system. Borsa Istanbul Review, 22, S92-S107. https://doi.org/10.1016/j.bir.2022.09.008 DOI: https://doi.org/10.1016/j.bir.2022.09.008
Albaity, M., Mallek, R. S., Bakather, A., & Al-Tamimi, H. A. H. (2023). Heterogeneity of the MENA region's bank stock returns: Does country risk matter?. Journal of Open Innovation: Technology, Market, and Complexity, 9(2), 100057. https://doi.org/10.1016/j.joitmc.2023.100057 DOI: https://doi.org/10.1016/j.joitmc.2023.100057
Azwar, P., & Tyers, R. (2015). Indonesian macro policy through two crises. Journal of Southeast Asian Economies, 37(2), 101-134. https://doi.org/10.2139/ssrn.2610963 DOI: https://doi.org/10.1355/ae37-2a
Bank Indonesia. (2015). Peraturan Bank Indonesia nomor 17/10/PBI/2015 tentang rasio loan to value atau rasio financing. Jakarta: Bank Indonesia.
Berg, A., & Pattillo, C. (1999). Are currency crises predictable? A test. IMF Staff papers, 46(2), 107-138. https://doi.org/10.2307/3867664 DOI: https://doi.org/10.2307/3867664
Bespalova, O. (2015). The Good, the Bad, and the Ugly signals of currency crises: Does the signal approach work in ex-ante forecasting of currency crises?.
Caldera-Sánchez, A., de Serres, A., Gori, F., & Röhn, O. (2017). Strengthening economic resilience: Insights from the post-1970 record of severe recessions and financial crises. OECD Economic Policy Paper, 20, 1-29. https://doi.org/10.1787/6b748a4b-en DOI: https://doi.org/10.1787/6b748a4b-en
Domala, V., & Kim, T. W. (2023). Application of empirical mode decomposition and Hodrick-Prescott filter for the prediction of single-step and multistep significant wave height with LSTM. Ocean Engineering, 285,115229. https://doi.org/10.1016/j.oceaneng.2023.115229 DOI: https://doi.org/10.1016/j.oceaneng.2023.115229
Fitri, R. M., & Hafiz, S. G. (2022). Determinants analysis of Islamic and conventional banks' systemic risk potential: A preliminary study. Studies in Business and Economics, 17(1), 202-217. https://doi.org/10.2478/sbe-2022-0014 DOI: https://doi.org/10.2478/sbe-2022-0014
Fu, K., Xia, J. B., Zhang, X. Y., & Shen, J. (2017). System structural analysis of communication networks based on DEMATEL-ISM and entropy. Journal of Central South University, 24(7), 1594-1601. https://doi.org/10.1007/s11771-017-3564-z DOI: https://doi.org/10.1007/s11771-017-3564-z
Gabus, A., & Fontela, E. (1973). Perceptions of the world problem atique: Communication procedure, communicating with those bearing collective responsibility. DEMATEL Report No.1, Battelle Geneva Research Centre, Geneva.
Ghosh, R., Ahmed, T., & Khan, Z. I. (2020). Assessing the resilience of the banking system of Bangladesh: A micro stress testing approach. European Journal of Applied Business and Management, 6(2), 1-34. https://doi.org/10.58869/EJABM DOI: https://doi.org/10.58869/EJABM
Granger, C. W. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica: Journal of the Econometric Society, 37(3), 424-438. https://doi.org/10.2307/1912791 DOI: https://doi.org/10.2307/1912791
Gupta, N., & Kumar, A. (2022). Comparing parametric, semi-parametric and non-parametric early warning systems for banking crisis: Indian context. Global Business and Economics Review, 26(2), 111-134. DOI: https://doi.org/10.1504/GBER.2022.120998
Handoyo, R. D., Erlando, A., & Astutik, N. T. (2020). Analysis of the twin deficits hypothesis in Indonesia and its impact on the financial crisis. Heliyon, 6(1). DOI: https://doi.org/10.1016/j.heliyon.2020.e03248
Kaminsky, G. L., & Reinhart, C. M. (1999). The twin crises: The causes of banking and balance-of-payments problems. American Economic Review, 89(3), 473-500. https://doi.org/10.1257/aer.89.3.473 DOI: https://doi.org/10.1257/aer.89.3.473
Kanas, A., Vasiliou, D., & Eriotis, N. (2012). Revisiting bank profitability: A semi-parametric approach. Journal of International Financial Markets, Institutions and Money, 22(4), 990-1005. https://doi.org/10.1016/j.intfin.2011.10.003 DOI: https://doi.org/10.1016/j.intfin.2011.10.003
Khan, A., Chaudhry, I. S., & Saeed, S. (2019). Islamic VS conventional commercial banking: The resilience avant-garde. Journal of Accounting and Finance in Emerging Economies, 5(2), 261-274. https://doi.org/10.26710/jafee.v5i2.921 DOI: https://doi.org/10.26710/jafee.v5i2.921
Maliha, H., & Marlina, L. (2019). Why are Islamic banks relatively more resilient to crises?. Ekonomi Islam Indonesia, 1(1), 34-55. https://doi.org/10.58968/eii.v1i1.3 DOI: https://doi.org/10.58968/eii.v1i1.3
Nugroho, M. R., Kurnia, A. S., Qoyum, A., & Fardila, F. (2020). The resilience of the Indonesian banking system and macroeconomic fluctuation: Islamic versus conventional banking. Journal of Islamic Monetary Economics and Finance, 6(2), 419-438. https://doi.org/10.21098/jimf.v6i2.1135 DOI: https://doi.org/10.21098/jimf.v6i2.1135
Özdemirci, F., Yüksel, S., Dinçer, H., & Eti, S. (2023). An assessment of alternative social banking systems using T-Spherical fuzzy TOP-DEMATEL approach. Decision Analytics Journal, 6, 100184. DOI: https://doi.org/10.1016/j.dajour.2023.100184
Pratama, S. D., & Rizal, R. (2019). The resilience of Islamic banks in facing the economic dynamics in Indonesia. Journal of Accounting and Finance in Emerging Economies, 5(2), 261-274. http://dx.doi.org/10.26710/jafee.v5i2.921 DOI: https://doi.org/10.2139/ssrn.3311990
Ravn, M. O., & Uhlig, H. (2002). On adjusting the Hodrick-Prescott filter for the frequency of observations. Review of Economics and Statistics, 84(2), 371-376. https://doi.org/10.1162/003465302317411604 DOI: https://doi.org/10.1162/003465302317411604
Saaty, T.L., (1990). How to make a decision: The analytic hierarchy process. European Journal of Operational Research, 48(1), 9-26. https://doi.org/10.1016/0377-2217(90)90057-I DOI: https://doi.org/10.1016/0377-2217(90)90057-I
Seker, S., & Zavadskas, E. K. (2017). Application of fuzzy DEMATEL method for analysing occupational risks on construction sites. Sustainability, 9(11), 2083. https://doi.org/10.3390/su9112083 DOI: https://doi.org/10.3390/su9112083
Setyawati, I., Widyastuti, T., & Suryati, A. (2019, October). Sharia Bank Resilience in Facing Macroeconomic Factors. 2019 International Conference on Organizational Innovation (ICOI 2019), Indonesia, 15-20. https://doi.org/10.2991/icoi-19.2019.4 DOI: https://doi.org/10.2991/icoi-19.2019.4
Setyawati, I., Karyatun, S., Awaludin, D. T., & Wiweka, K. (2022). Stability and resilience of the Islamic banking system: A closer look at the macroeconomic effects. Calitatea, 23(187), 295-304. https://doi.org/10.47750/QAS/23.187.36 DOI: https://doi.org/10.47750/QAS/23.187.36
Shakeri, H., Khalilzadeh, M., Raslanas, S., & Kazimieras Zavadskas, E. (2021). What do project managers need to know to succeed in face-to-face communication?. Economic research-Ekonomska istraživanja, 34(1), 1094-1120. https://doi.org/10.1080/1331677X.2020.1819851 DOI: https://doi.org/10.1080/1331677X.2020.1819851
Wiranatakusuma, D. B. (2018). Constructing the Islamic banking resilience index in Indonesia. Journal of Islamic Monetary Economics and Finance, 3, 45-62. https://doi.org/10.21098/jimf.v3i0.760 DOI: https://doi.org/10.21098/jimf.v3i0.760
