Data Envelopment Analysis Approach for Efficiency Comparison of Banking System


Rendra Erdkhadifa
Risdiana Himmati


This study aims to calculate the level of banking efficiency that needs to be known to be associated with the performance of the banking management macro and micro variable. So banking industry in practice can arrange a program to increase efficiency and to anticipate the influence of anything that can makes banking will be lost .Bank with a good the efficiency in general is able to provide good service for customer. Efficiency of bank usually set pricing with the form of the high interest margin .The variables input used in this research is amount of labor .And the output to calculate efficiency are interest income of the money and the amount of funds which has been distributed. Then, comparing two different principle banking between bank syariah mandiri and bank mandiri. By using the method of measurement efficiency with DEA CCR, in two banks was efficient in some specified time. And then using DEA aggressive appears that the efficiency that tends to look the differences between DMU from both banks. From the, observation bank Syariah mandiri is much better because it can reach effieciency 12nd DMU. If calculating unefficiency that bank syariah mandiri also is better than bank mandiri.


How to Cite
, R. E., & Himmati, R. (2022). Data Envelopment Analysis Approach for Efficiency Comparison of Banking System. Enrichment : Journal of Management, 12(2), 1584-1592. Retrieved from


Al-Refaie, A, & Li, M, H. (2008). Solving the Multiresponse Problem in Taguchi Method by Aggressive Formulation in DEA, Proceedings of the World Congress on Engineering Vol II, London.
Angiz, M. Z., Mustafa, A., & Kamali, M, J .(2013). ‘Cross-ranking of Decision Making Units in Data Envelopment Analysis’, Applied Mathematical Modelling no. 37, hh. 398–405.
Azadeh, A., Ghaderi, S. F., Mirjalili, M., & Moghaddam, M. (2011). ‘Integration of Analytic Hierarchy Process and Data Envelopment Analysis for Assessment and Optimization of Personnel Productivity In A Large Industrial Bank’, Expert Systems with Applications, no. 38, hh. 5212–5225.
Charnes, A., Cooper, W. W., & Rhodes, E. (1978). ‘Measuring The Efficiency Of Decision Making Units’, European Journal of Operational Research, no. 2, hh. 429-444.
Deliktas, E & Günal, G, G (2016). ‘Economic Growth and Input Use Efficiency in Low, Upper – Middle and High Incomed Countries (1991-2011) : A Data Envelopment Analysis’, Procedia Economics and Finance, no. 38, hh. 308 – 317.
Draper, N, R, & Smith, H. (1998). Applied regression analysis : third edition, John Wiley & Sons, Inc, Canada
Doyle, J, & Green, R. (1994) ‘Efficiency and Cross-Efficiency in DEA: Derivations, Meanings and Uses’, The Journal of the Operational Research Society, Vol. 45, no. 5, hh. 567-578
Dyson, R., G, & Thanassoulis, E. (1988). ‘Reducing Weight Flexibility in Data Envelopment Analysis’, The Journal of the Operational Research Society, Vol. 39, no. 6, hh. 563-576
Erdkhadifa, R. (2013). Optimasi Multirespon Dengan Menggunakan Metode Ganungan Data Envelopment Analysis (DEA) Aggressive dan Response Surface (Studi Kasus: PT. Phillips Indonesia). FMIPA ITS, Surabaya.
Ertay, T, & Ruan, D. (2005). ‘Data Envelopment Analysis Based Decision Model For Optimal Operator Allocation In CMS’, European Journal of Operational Research, no. 164, hh. 800–810.
Hadad, Muliaman. Santoso, Wimboh. Ilyas Dhaniel, Mardamugraha, E. (2003) ‘Analisis Efisiensi Industri Perbankan BI’.
Hong, H, S, H, Shin, C, K, Park, S, C, & Kim, S, H (1999). ‘Evaluating The Efficiency of System Integration Projects Using Data Envelopment Analysis (DEA) and Machine Learning’, Expert Systems with Applications, no. 16, hh. 283–296.
Karsinah and Cahya, A, R, K. (2012) ‘Kinerja Bank Umum Syariah di Indonesia Tahun 2010-2012’, JEJAK Journal of Economics and Policy, Vol. 5(2), hh. 117–229.
Mousavi-Avval, S, H, Rafiee, S, Jafari, A, & Mohammadi, A. (2011). Improving Energy Use Efficiency of Canola Production Using Data Envelopment Analysis (DEA) Approach, Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj.
Muljawan, D. et al (2014). ‘Faktor-Faktor Penentu Efisiensi Kredit’, hh. 1076.
Yannick, G, S, Z, Hongzhong , Z, & Thierry, B. (2016). ‘Technical efficiency assessment using data envelopment analysis: an application to the banking sektor of Côte d’Ivoire’, Procedia - Social and Behavioral Sciences, no. 235, hh. 198 – 207.
Yilmaz, A & Günes, N. (2015) ‘Efficiency Comparison of Participation and Conventional Banking Sektors in Turkey between 2007-2013’, Procedia - Social and Behavioral Sciences, no. 195, hh. 383 – 392.