Article Sidebar

Download
Full text PDF
Statistic
Read Counter : 666 Download : 750

Downloads

Download data is not yet available.

Main Article Content

Abstract

Purpose – The purpose of this study was to determine the extent of the impact of Covid-19 on the macroeconomic indicators and financial performance of Islamic banks in Indonesia. The results of this study may serve as a reference for the Indonesian government and Islamic banks’ stakeholders in formulating strategic decisions in creating innovative solutions during the Covid-19 pandemic.
Methodology – Quantitative research method with 2 approaches, namely Partial Least Square-Structural Equation Modeling (PLS-SEM) and Artificial Neural Networks (ANN) was selected for this study.
Findings – This study demonstrated that macroeconomic indicators were significantly affected by the Covid-19 pandemic. However, the results of the ANN and PLS-SEM models varied. The PLS-SEM model illustrated the impact of the Covid-19 pandemic affecting the performance of Islamic banking, while the ANN model did not.
Implication – This research has implications for stakeholders, especially the government to maintain macroeconomic stability, while for Islamic banking management to focus more on product innovation and service excellence so that it can be closer to the public, especially Muslims community.
Originality – Numerous studies examining macroeconomics and the financial performance of Islamic banking have been conducted. This study aimed to offer an alternative perspective by using two models, namely PLS-SEM and ANN.

Keywords

Pandemic COVID-19 Macroeconomics Financial Performance PLS-SEM ANN

Article Details

License

Copyright (c) 2022 Ulumuddin Nurul Fakhri, Aminah Nuriyah

Creative Commons License

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

Authors who publish with this journal agree to the following terms:

  1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
  2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
  3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
Author Biographies

Ulumuddin Nurul Fakhri, Mahad Aly An-Nuaimy, Jakarta, Indonesia

Lecturer

Aminah Nuriyah, Department of Islamic Business Management, Faculty of Business Management, Institut Agama Islam Tazkia, Bogor, Indonesia

Lecturer

How to Cite
Fakhri, U. N., & Nuriyah, A. (2022). The impacts of Covid-19 on macroeconomic indicators and the performance of Islamic banks in Indonesia. Jurnal Ekonomi & Keuangan Islam, 8(2), 206–220. https://doi.org/10.20885/JEKI.vol8.iss2.art5
Download Citation
Endnote/Zotero/Mendeley (RIS)
BibTeX
Crossref
Scopus
Google Scholar
Europe PMC

References

  1. Abbasi GA, Tiew LY, Tang J, Goh Y-N, & Thurasamy R. (2021). The adoption of cryptocurrency as a disruptive force: Deep learning-based dual stage structural equation modelling and artificial neural network analysis. PLoS ONE, 16(3). https://doi.org/10.1371/journal.pone.0247582.
  2. Al-Emran, M., Mezhuyev, V., & Kamaludin, A. (2018). PLS-SEM in information systems research: A comprehensive methodological reference. Advanced Intelligent Systems and Informatics, 644-653. https://doi.org./10.1007/978-3-319-99010-1_59
  3. Amah, N., & Hendriana, S. (2017). Determinan loyalitas nasabah (studi pada bank syariah di Kota Madiun). Assets: Jurnal Akuntansi dan Pendidikan, 5(2), 161-172. http://doi.org/10.25273/jap.v5i2.1196.
  4. Badan Pusat Statistik. (2020). Pertumbuhan ekonomi Indonesia triwulan IV-2020. No. 13/02/Th. Badan Pusat Statistik XXIV. www.bps.go.id..
  5. Bairoliya, N., & Imrohoroglu, A. (2020). Covid-19: Mitigation measures and the aftershock in an overlapping generations model. SSRN Electronic Journal. http://dx.doi.org/10.2139/ssrn.3737173
  6. Bank Indonesia. (2020). Laporan tahunan 2020. Bank Indonesia. https://www.bi.go.id/id/publikasi/laporan/Documents/Laporan-Akuntabilitas-Bank-Indonesia-2020.pdf
  7. Dumitrescu, B. A., Kagitci, M., & Cepoi, C. O. (2021). Nonlinear effects of public debt on inflation. Does the size of the shadow economy matter?. Finance Research Letters. https://doi.org/10.1016/j.frl.2021.102255.
  8. Dorman, P. (2014). Microeconomics. Springer-Verlag Berlin Heidelberg.
  9. Fakhri, U. N., & Darmawan, A. (2021). Comparison of Islamic and conventional banking financial performance during the covid-19 period. International Journal of Islamic Economics and Finance (IJIEF), 4(SI), 19-40. https://doi.org/10.18196/ijief.v4i0.10080.
  10. Fakhri, U. N., Anwar, S., & Ismal, R. (2020). Comparison of sharia and conventional banking bankruptcy rates in Indonesia. Tazkia Islamic Finance and Business Review, 13 (2), 125-141. DOI: https://doi.org/10.30993/tifbr.v13i2.193.
  11. Fakhri, U. N., Anwar, S., Ismal, R., & Ascarya, A. (2019). Comparison and predicting financial performance of Islamic and conventional banks in Indonesia to achieve growth sustainability. al-Uqud: Journal of Islamic Economics, 3(2), 174-187. https://doi.org/10.26740/al-uqud.v3n2.p174-187.
  12. Fakhrunnas, F. (2019). The effect of macroeconomic and bank-specific variables to risk-taking of Islamic bank in Indonesia. International Journal of Islamic Economics and Finance (IJIEF), 1(2), 165-186. https://doi.org/10.18196/ijief.129.
  13. Fontana, G., McCombie, J., & Sawyer, M. (2010). Macroeconomics, finance and money: Essays in honour of Philip Arestis. Springer.
  14. Hair, J.F., M. Sarstedt, C.M. Ringle., & S.P. Gudergan. (2018). Advanced issues in partial least squares structural equation modeling (PLS-SEM). Sage Publications.
  15. Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: A review of four recent studies. Strategic Management Journal, 20(2), 195–204. https://doi.org/10.1002/(SICI)1097-0266(199902)20:2<195::AID-SMJ13>3.0.CO;2-7.
  16. Hsu, S. H., Chen, W. H., & Hsieh, M. J. (2006). Robustness testing of PLS, LISREL, EQS and ANN-based SEM for measuring customer satisfaction. Total Quality Management & Business Excellence, 17(3), 355-372. https://doi.org/10.1080/14783360500451465.
  17. Ichsan, R. N., Suparmin, S., Yusuf, M., Ismal, R., & Sitompul, S. (2021). Determinant of sharia bank's financial performance during the Covid-19 pandemic. Budapest International Research and Critics Institute (BIRCI-Journal): Humanities and Social Sciences, 4(1), 298-309. https://doi.org/10.33258/birci.v4i1.1594.
  18. Iyke, B. N., & Ho, S. Y. (2021). Exchange rate exposure in the South African stock market before and during the Covid-19 pandemic. Finance Research Letters, 102000. 1-9.: https://doi.org/10.1016/j.frl.2021.102000.
  19. Jelilov, G., Iorember, P. T., Usman, O., & Yua, P. M. (2020). Testing the nexus between stock market returns and inflation in Nigeria: Does the effect of Covid-19 pandemic matter?. Journal of Public Affairs, 1-9. https://doi.org/10.1002/pa.2289.
  20. Luwihono, A., Suherman, B., Sembiring, D., Rasyid, S., Kalbuana, N., Saputro, R., Prasetyo, B., Taryana, T., Suprihartini, Y., Asih, P., Mahfud, Z & Rusdiyanto, R. (2021). Macroeconomic effect on stock price: Evidence from Indonesia. Accounting, 7(5), 1189-1202. https://doi.org/10.5267/j.ac.2021.2.019
  21. Murad, H., Ali, S. B., Baig, U., Raza, A., Ali, S., & Abdullah, A. (2021). Comparative study: conventional and Islamic banking performance in Pakistan. International Journal of Management (IJM), 12(3). 448-459. https://doi.org/10.34218/IJM.12.3.2021.042.
  22. Nurhuda, M. R., Rozali, M., Rakhmatillah, L., & Adinugraha, H. H. (2020). Does the pruning on the reference interest rate by bank Indonesia influence interest rate sensitivity towards banking net interest margin during early period in facing Covid-19 in Indonesia?. Annals of the University of Craiova for Journalism, Communication and Management, 6(1), 13-30. https://aucjc.ro/wp-content/uploads/2020/12/aucjcm-vol6-13-30.pdf
  23. Ochozka, M., Horák, J., & Šuleř, P. (2019). Equalizing seasonal time series using artificial neural networks in predicting the Euro–Yuan exchange rate. Journal of Risk and Financial Management, 12(2), 76. https://doi.org/10.3390/jrfm12020076.
  24. Ohyama, M. (2016). Macroeconomics, Trade, and Social Welfare. Springer Japan.
  25. Olivia, S., Gibson, J., & Nasrudin, R. A. (2020). Indonesia in the time of Covid-19. Bulletin of Indonesian Economic Studies, 56(2), 143-174. https://doi.org/10.1080/00074918.2020.1798581.
  26. Prasetyo, B. (2006). Metode penelitian kuantitatif teori dan aplikasi. Raja Grafindo Persada.
  27. Rahman, T., & Santoso, A. (2019). Determinants of Islamic banking performance: An empirical study in Indonesia. Muqtasid: Jurnal Ekonomi dan Perbankan Syariah, 10(2), 139-154. https://doi.org/10.18326/muqtasid.v10i2.139-154.
  28. Riono, P. (2020). UI ungkap kronologi negara abai virus corona masuk RI Januari. CNN https://www.cnnindonesia.com/teknologi/20200420160222-199-495344/ui-ungkap-kronologi-negara-abai-virus-corona-masuk-ri-januari
  29. Sholihin, M., & Ratmono, D. (2021). Analisis SEM-PLS dengan WarpPLS 7.0 untuk Hubungan Nonlinier dalam Penelitian Sosial dan Bisnis. Andi Offset
  30. Setyawati, I., Suroso, S., Suryanto, T., & Nurjannah, D. S. (2017). Does financial performance of Islamic banking is better? Panel data estimation. European Research Studies Journal 20(2A), https://www.ersj.eu/repec/ers/papers/17_2_A_p36.pdf
  31. Sugandi, E. A. (2020). Indonesia’s financial markets and monetary policy dynamics amid the Covid-19 pandemic. ADBI Working Paper. 1198. http://dx.doi.org/10.2139/ssrn.3712774.
  32. Syahri, A., & Robiyanto, R. (2020). The correlation of gold, exchange rate, and stock market on Covid-19 pandemic period. Jurnal Keuangan dan Perbankan, 24(3), 350-362. https://doi.org/10.26905/jkdp.v24i3.4621.
  33. Taylor, L. (2021). Reconstructing macroeconomics. Harvard University Press.
  34. Vochozka, M., Horak, J., & Suler, P. (2019). Equalizing seasonal time series using artificial neural networks in predicting the Euro-Yuan exchange rate. Journal of Risk and Financial Management, 12(2), 1-17. https://doi.org/10.3390/jrfm12020076
  35. Walmsley, T. L., Rose, A., & Wei, D. (2020). Impacts on the US macroeconomy of mandatory business closures in response to the Covid-19 Pandemic. Applied Economics Letters, 1-8. https://doi.org/10.1080/13504851.2020.1809626.
  36. World Health Organization. (2020). Coronavirus Disease. World Health Organization https://www.who.int/emergencies/diseases/novel-coronavirus-2019
  37. Wunder, S., Kaimowitz, D., Jensen, S., & Feder, S. (2021). Coronavirus, macroeconomy, and forests: What likely impacts?. Forest Policy and Economics, 131, 102536. https://doi.org/10.1016/j.forpol.2021.102536.
  38. Yamin, S., & Kurniawan, H. (2011). Generasi baru mengolah data penelitian dengan partial least square path modeling. Salemba Infotek.
  39. Yunita, P. (2020). The future of Indonesia Islamic banking industry: Bankruptcy analyzing the second wave of global financial crisis. International Journal of Islamic Economics and Finance (IJIEF), 3(2), 199-226. https://doi.org/10.18196/ijief.3227.
  40. Yusuf, M., & Ichsan, R. N. (2021). Analysis of banking performance in the aftermath of the merger of bank syariah Indonesia in Covid 19. International Journal of Science, Technology & Management, 2(2), 472-478. https://doi.org/10.46729/ijstm.v2i2.182.
  41. Zhang, Y., Diao, X., Chen, K.Z., Robinson, S. & Fan, S. (2020). Impact of Covid-19 on China's macroeconomy and agri-food system – an economy-wide multiplier model analysis. China Agricultural Economic Review, 12(3), 387-407. https://doi.org/10.1108/CAER-04-2020-0063.
  42. Zhang, H., Wu, W., & Yao, M. (2012). Boundedness and convergence of batch back-propagation algorithm with penalty for feedforward neural networks. Neurocomputing. 89, 141-146. https://doi.org/10.1016/j.neucom.2012.02.029.