A Comparison of Principal Component Analysis and Maximum Likelihood Factor Analysis in Bank Health Ratio

  • Firdaus Firdaus University of Bengkulu
  • Sigit Nugroho University of Bengkulu
  • Haryo Widodo University of Bengkulu


The use of factor analysis methods to reduce variable dimensions is generally known and has been used in various disciplines. The two famous extraction methods of factor analysis are principal component analysis and maximum likelihood. This study aimed to compare both, principal component analysis and maximum likelihood. By their constructed matrix correlation, applied to bank financial ratios. The study is developed from an initial set of 22 ratios of healthy indexed banks. The use of bank financial data aims to identify the structure of the financial ratio of healthy indexed banks. There are 10 variables satisfying the criteria of factor analysis techniques to be considered in the analysis. Both principal component analysis and maximum likelihood suggest three factors that can be used to represent 10 variables.
Keywords: factor analysis; principal component analysis; maximum likelihood; financial ratios; bank health.


Ardiningsih, S. (2001). Perangkat dan Teknik Analisis Investasi di Pasar Modal. Bursa EFek Jakarta.

Brien, C. J. (1988). An Analysis of Correlation Matrices : Variables Cross-Classified by Two Factors. Biometrika, 75(3): 469-476.

Bugli, C., & Lambert, P. (2007). Comparison Between Principal Component Analysis and Independent Component Analysis in Electroencephalograms Modelling. Biometrical Journal, 49(2): 312-327.

Dable, B. K., & Booksh, K. S. (2001). Selecting Significant Factors by The Noise Addition Method in Principal Component Analysis. Journal of Chemometrics, 15(7): 591-613.

Everitt, B. S. (2005). Book Review: An R and S-PLUS Companion to Multivariate Analysis. In Applied Psychological Measurement (Vol. 35, Issue 7). Springer-Verlag.

Grover, Martha A.; Barthe, Stephanie C.; Rousseau, R. W. (2009). Principal Component Analysis for Estimating Population Density from Chord-Length Density. AIChE Journal, 55(9): 2260-2270.

Härdle, W. K., & Simar, L. (2019). Applied Multivariate Statistical Analysis. In Applied Multivariate Statistical Analysis.

Ho, P., Silva, M. C. M., & Hogg, T. A. (2001). Multiple Imputation and Maximum Likelihood Principal Component Analysis of Incomplete Multivariate Data From A Study of The Ageing of Port. Chemometrics and Intelligent Laboratory Systems, 55(1-2): 1-11.

Johnson, R. A., & Wichern, D. W. (2007). Applied Multivariate Statistics (p. 776). Pearson Prentice Hall - Upper Saddle River, N.J.

Joliffe, I. T. (2010). Principal Components Analysis. In International Encyclopedia of Education. Springer-Verlag.

Lehmann, A., Scheffler, C., & Hermanussen, M. (2010). Evidence of Seasonal Variation in Longitudinal Growth of Height in A Sample of Boys From Stuttgart Carlsschule, 1771-1793, Using Combined Principal Component Analysis and Maximum Likelihood Principle. HOMO- Journal of Comparative Human Biology, 61(1): 59-63.

Modarres, R., & Jernigan, R. W. (1992). Testing The Equality of Correlation Matrices. Communications in Statistics - Theory and Methods, 21(8): 2107–2125.

Rencher, A. C. (1998). Multivariate Statistical Inference and Applications. In Technometrics (Vol. 40, Issue 4). Jhon Wiley & Sons, Inc.

Taylor, P., & Jennrich, R. I. (2012). Journal of the American Statistical Association An Asymptotic χ Test for the Equality of Two Correlation Matrices. April 2013, 37-41.

White, P. R., Tan, M. H., & Hammond, J. K. (2006). Analysis of The Maximum Likelihood, Total Least Squares and Principal Component Approaches For Frequency Response Function Estimation. Journal of Sound and Vibration, 290(3-5): 676-689.
How to Cite
FIRDAUS, Firdaus; NUGROHO, Sigit; WIDODO, Haryo. A Comparison of Principal Component Analysis and Maximum Likelihood Factor Analysis in Bank Health Ratio. Jurnal ILMU DASAR, [S.l.], v. 22, n. 2, p. 147-152, july 2021. ISSN 2442-5613. Available at: <https://jurnal.unej.ac.id/index.php/JID/article/view/13487>. Date accessed: 27 sep. 2021. doi: https://doi.org/10.19184/jid.v22i2.13487.