Panel data regression analysis utilizing CEM and FEM methods in relation to the profitability of Sharia commercial banks (2015 – 2024)

Authors

  • Mahfudhotin Sharia Banking Study Program, UIN Syekh Wasil Kediri, East Java, Indonesia
  • Kiky Novita Sari Sharia Banking Study Program, UIN Syekh Wasil Kediri, East Java, Indonesia

DOI:

https://doi.org/10.30762/f_m.v8i2.5633

Keywords:

Panel Data Regression Analysis, Fixed Effect Model, Common Effect Model, Return on Assets, Chow Test

Abstract

Panel data regression analysis is typically utilized to investigate individuals or entities over different time spans. In this research, the regression models applied to the panel data include the Common Effect Model (CEM) and the Fixed Effect Model (FEM). To evaluate which model is superior to the other, the Chow test estimation method was utilized. This evaluation focused on the Return on Assets profitability data from nine Islamic Commercial Banks during the timeframe from 2015 to 2024. The findings from the Chow test analysis indicated that the Common Effect Model was the most suitable, with Non-Performing Financing identified as a significant factor influencing profitability (Return on Assets) in the Islamic Commercial Banks registered with the Financial Services Authority.

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References

Abdillah, E., & Septianawati, E. (2023). Structural equation modeling (SEM) on mechanisms of non science students’ attitudes toward statistics courses. Journal Focus Action of Research Mathematic (Factor M), 6(2), 27–42. https://doi.org/10.30762/f_m.v6i2.1987

Afifah, A. ., Hamidah, D. ., & Burhani, I. . (2019). Studi Komparasi Tingkat Kepercayaan Diri (Self Confidence) Siswa Antara Kelas Homogen Dengan Kelas Heterogen Di Sekolah Menengah Atas. Happiness: Journal of Psychology and Islamic Science, 3(1), 44–47. https://doi.org/10.30762/happiness.v3i1.352

Ahadiyah, K., & Dewi, A. F. (2022). Perbandingan model Generalized Ammi (GAMMI) dengan row column interaction model pada interaksi genotipe dan lingkungan. Journal Focus Action of Research Mathematic (Factor M), 4(2), 27–42. https://doi.org/10.30762/factor_m.v4i2.4193

Anisa, A., & Ilyas, N. (2012). Analisis data panel model efek acak pada data kemiskinan di Provinsi Sulawesi Selatan. Jurnal Matematika, Statistika dan Komputasi, 8(2), 110–130. https://doi.org/10.20956/jmsk.v8i2.3391

Aryanto, W., & Handaka, R. D. (2017). Analisis pengaruh belanja modal, indeks pembangunan manusia, dan tenaga kerja terserap terhadap pertumbuhan ekonomi kabupaten/kota di Indonesia. Jurnal Akuntansi Manajerial, 2(2), 52–63. https://doi.org/10.52447/jam.v2i2.932

Baltagi, B. H. (2008). Econometrics (4th ed.). Springer.

Basuki, A. T., & Prawoto, N. (2016). Analisis regresi dilengkapi aplikasi SPSS dan Eviews. Rajawali Pers.

Basuki, A. T., & Prawoto, N. (2017). Analisis regresi dalam penelitian ekonomi dan bisnis. PT Rajagrafindo Persada.

Buhaerah, P. (2017). Pengaruh finansialisasi terhadap ketimpangan pendapatan di ASEAN: Analisis data panel. Bulletin of Monetary Economics and Banking, 19(3), 335–352. https://doi.org/10.21098/bemp.v19i3.669

Desmawan, D., Syaifudin, R., Sari, T. N., Mamola, R., Haya, H., & Setyadi, S. (2021). Faktor dominan relativitas kemiskinan: Pendekatan analisis data panel. Media Sains Indonesia.

Dettori, J. R., Norvell, D. C., & Chapman, J. R. (2022). Fixed-effect vs random-effects models for meta-analysis: 3 points to consider. Global Spine Journal, 12(7). https://doi.org/10.1177/21925682221110527

Ghozali, I. (2018). Aplikasi analisis multivariate dengan program IBM SPSS 25. Badan Penerbit Universitas Diponegoro.

Hamdani, S. P., Yuliandari, W. S., & Budiono, E. (2017). Kepemilikan saham publik dan return on assets terhadap pengungkapan corporate social responsibility. JRAK, 9(1), 47. https://doi.org/10.23969/jrak.v9i1.368

Hutagalung, I. P. (2022). Analisis regresi data panel dengan pendekatan Common Effect Model (CEM), Fixed Effect Model (FEM) dan Random Effect Model (REM) (Studi kasus: IPM Sumatera Utara periode 2014–2020) [Undergraduate thesis]. Universitas Sumatera Utara.

Ilham, R. N., Sadalia, I., Irawati, N., & Sinta, I. (2022). Risk and return model of digital cryptocurrency asset investment in Indonesia. Al Qalam: Jurnal Ilmiah Keagamaan dan Kemasyarakatan, 16(1), 357–376. http://dx.doi.org/10.35931/aq.v16i1.854

Jaya, I. G. N. M., & Sunengsih, N. (2009). Kajian analisis regresi dengan data panel. Prosiding Seminar Nasional Penelitian, 51–58. Universitas Negeri Yogyakarta. https://eprints.uny.ac.id/12187/1/M_Stat_6_GEDE%20NYOMAN.pdf

Ko, F. S. (2022). Comparisons of a multi-regional trial for four or five regions by fixed effect model and random effect model about allocating sample size rationally into individual regions for a multi-regional trial. Communications in Statistics-Theory and Methods, 1–21. https://doi.org/10.1080/03610926.2022.2065019

Mahfudhotin, M. (2020). Analisa pertumbuhan tenaga kerja dan jaringan kantor terhadap perkembangan aset perbankan syariah. El-Qist: Journal of Islamic Economics and Business (JIEB), 9(1), 1–15. https://doi.org/10.15642/elqist.2019.9.1.1-15

Mahfudhotin, M. (2023). Forecasting plafond dengan time series pada kredit multiguna di PT. Bank Jatim Cabang RSU dr. Soetomo Surabaya. Fraction: Jurnal Teori dan Terapan Matematika, 3(1), 14–22. https://doi.org/10.33019/fraction.v3i1.37

Mobonggi, I. D., Achmad, N., Resmawan, & Hasan, K. I. (2022). Analisis regresi data panel dengan pendekatan Common Effect Model dan Fixed Effect Model pada kasus produksi tanaman jagung. INTERVAL: Jurnal Ilmiah Matematika, 2(2), 52–57. https://doi.org/10.33751/interval.v2i2.6516

Patterkadavan, F. P., & Qayed, S. H. (2022). Determinants of maternal mortality: An empirical study of Indian states based on the random effect model analysis. National Journal of Community Medicine, 13(08), 532–541. https://doi.org/10.55489/njcm.130820222203

Rahmadeni, R., & Wulandari, N. (2017). Analisis faktor-faktor yang mempengaruhi inflasi pada kota metropolitan di Indonesia dengan menggunakan analisis data panel. Jurnal Sains Matematika Dan Statistika, 3(2), 34–42. http://dx.doi.org/10.24014/jsms.v3i2.4475

Ruth, A. M., & Syofyan, S. (2014). Faktor penentu foreign direct investment di ASEAN-7; Analisis data panel, 2000-2012. Media Ekonomi, 22(1), 95–121. http://www.trijurnal.lemlit.trisakti.ac.id/index.php/medek/article/view/841

Sitompul, S., Ichsan, R. N., & Nasution, L. (2021). The influence of exchange rate, inflation, for the results of the development assets of Islamic banks. Journal of Economics, Finance And Management Studies, 4(3), 138–148. https://doi.org/10.47191/jefms/v4-i3-05

Sofian, & Susanto. (2024). Determinants of Islamic bank profitability in Indonesia.

Sriyana, J. (2014). Metode regresi data panel. Ekonisia.

Stephanie, Sistomo, & Simanjuntak, R. P. (2018). Analisis faktor-faktor yang mempengaruhi. Fundamental Management Journal, 2(1).

Sutikno, B., Faruk, A., & Dwipurwani, O. (2017). Penerapan regresi data panel komponen satu arah untuk menentukan faktor-faktor yang mempengaruhi indeks pembangunan manusia. Jurnal Matematika Integratif, 13(1), 1–10. https://doi.org/10.24198/jmi.v13.n1.11383.1-10

Widodo, E., Suriani, E., & Kusumandari, G. E. (2019). Analisis Regresi Panel pada Kasus Kemiskinan di Indonesia. PRISMA, Prosiding Seminar Nasional Matematika, 2, 710-717. https://journal.unnes.ac.id/sju/prisma/article/view/29257

Wulan, E. R., & Anggraini, R. E. . (2019). Gaya Kognitif Field-Dependent dan Field-Independent sebagai Jendela Profil Pemecahan Masalah Polya dari Siswa SMP. Journal Focus Action of Research Mathematic (Factor M), 1(2), 123–142. https://doi.org/10.30762/factor_m.v1i2.1503

Yuniar, I. A., & Kusrini, D. E. (2021). Penerapan regresi data panel dinamis untuk pemodelan ekspor dan impor di ASEAN. Seminar Nasional Official Statistics, 2021(2), 111–119.

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Published

14-12-2025

How to Cite

Mahfudhotin, & Sari, K. N. (2025). Panel data regression analysis utilizing CEM and FEM methods in relation to the profitability of Sharia commercial banks (2015 – 2024). Journal Focus Action of Research Mathematic (Factor M), 8(2), 242–261. https://doi.org/10.30762/f_m.v8i2.5633