BUKU: Strategic Performance Management and Measurement Using Data Envelopment Analysis

Organizations can use the valuable tool of data envelopment analysis (DEA) to make informed decisions on developing successful strategies, setting specific goals, and identifying underperforming activities to improve the output or outcome of performance measurement.

Pengantar Umum DEA

DEA (Data Envelopment Analysis) is the optimization method of mathematical programming to generalize the Farrell(1957) single-input/ single-output technical efficiency measure to the multiple-input/ multiple-output case by constructing a relative efficiency score as the ratio of a single virtual output to a single virtual input. Thus DEA become a new tool in operational research for measuring technical efficiency. It originally was developed by Charnes, Cooper, Rhodes(1978) with CRS and was extended by Banker, Charnes, Cooper(1984) to include variable returns to scale. So the basic DEA models are known as CCR and BCC. 

Since 1978 over 1000 articles, books and dissertation have been published and DEA has rapidly extended to returns to scale, dummy or categorical variables, discretionary and non-discretionary variables, incorporating value judgments, longitudinal analysis, weight restrictions, stochastic DEA, non-parametric Malmquist indices, technical change in DEA and many other topics. 

Up to now the DEA measure has been used to evaluate and compare educational departments (schools, colleges and universities), health care (hospitals, clinics) prisons, agricultural production, banking, armed forces, sports, market research, transportation (highway maintenance), courts, benchmarking, index number construction and many other applications.At the moment researchers follow wide ranges of DEA and related topics.

IN-HOUSE TRAINING DAN KONSULTASI DEA UNTUK KORPORASI

PENDAHULUAN

Data Envelopment Analysis pertama kali diperkenalkan oleh Charnes, Cooper dan Rhodes pada tahun 1978 dan 1979. Semenjak itu pendekatan dengan menggunakan DEA ini banyak digunakan di dalam riset-riset operasional dan ilmu manajemen. Pendekatan DEA ini lebih menekankan kepada pendekatan yang berorientasi kepada tugas dan lebih difokuskan kepada tugas yang penting, yaitu mengevaluasi kinerja dari unit pembuat keputusan/UPK (decision making units). Semenjak tahun 1980an, pendekatan ini banyak digunakan untuk mengukur tingkat efisiensi dari industri perbankan secara nasional.

DEA merupakan suatu teknik program linier yang digunakan untuk mengevaluasi bagaimana suatu proses pengambilan keputusan dalam suatu unit beroperasi secara relatif dengan unit lain dalam sampel. Selanjutnya proses tersebut akan membentuk suatu garis frontier yang terbentuk dari unit-unit yang efisien yang kemudian dibandingkan dengan unit yang tidak efisien untuk menghasilkan nilai efisiensinya masing-masing.

Karena pentingnya metode riset ini, maka SMART CONSULTING bekerjasama dengan pihak manapun untuk mengadakan pelatihan selama 2 hari dalam rangka memenuhi kebutuhan para akademisi maupun praktisi yang hendak menggunakan metode DEA.

BOOK: DEA, Theory and Techniques for Economics and Operations Research, SUBHASH C. RAY

• By Subhash C. Ray
  University of Connecticut
  
  
• Publisher: Cambridge University Press
  Print Publication Year:2004
  Online Publication Date:November 2009
  Online ISBN:9780511606731
  Hardback ISBN:9780521802567

BUKU: Data Envelopment Analysis: Returns-to-Scale Measurement

The paper provides an overview of the different approaches to measure returns-to-scale (RTS) in Data Envelopment Analysis (DEA). DEA is a promising approach allowing for analysis of efficiency and RTS in certain fields where other concepts like regression analysis are not applicable. Therefore, DEA literature and especially literature on RTS measurement in DEA is rapidly growing. 

Returns-to- scale and scale efficiency can lead to significant and long-lasting implications for management and politics. Furthermore, RTS classification can be used to decide on mergers and acquisitions. Following the description of the most common DEA models and their technology different approaches to measure RTS are described and advantages and disadvantages are elaborated. 

The approaches are subdivided in qualitative and quantitative approaches and RTS measurement in cost-based and non- radial models. Additionally, sensitivity analysis for RTS measurement is being dealt with. Finally, an empirical application is provided to illustrate RTS measurement approaches discussed in the paper.

Analisis Perbandingan Tingkat Efisiensi BMT Kota Tasikmalaya Periode 2008-2012 dengan Pendekatan Two Stage Data Envelopment Analysis

Oleh: Asri Prihastuti 

This study measures the comparative efficiency of BMT Tasikmalaya during the period 2008-2012. The method used is Two Stage DEA with the intermediation approach. The first stage of measuring the efficiency of each BMT using DEA. Input variables used were total deposit, equity and total labour. While the variables output is total financing and operating income. The second stage determines factors influencing the efficiency of BMT using Tobit Method. The variables used were BOPO, ROA (Return on Equity) and EQAS.

            The results show that the overall efficiency of BMT in the year 2008 reached 0.88 and the next year (2009) to 2012 increased significantly to reach 0.96. While the level of technical efficiency has increased by fluctuations in 2008-2012. Means that the management of the financial operations of BMT during 2008-2012 is relatively inefficient. The main cause of inefficiency in the output-oriented measure is operating income which can be increasing by 59.96%. Tobit results show that BOPO and ROE has statistically significant positive impact on overall efficiency of BMT Tasikmalaya. While the power of capital (CAR) has no significant positive impact on the efficiency of BMT Tasikmalaya

Keywords: Data Envelopment Analysis (DEA), Efficiency, Baitul Mal wa Tamwil

BUKU: Mining Data Envelopment Analysis using Clustering Approach: for Heterogeneous Decision Making Units

This book integrates two important fields of information technology, data mining and data envelopment analysis (DEA), to provide a new tool for measuring the performance of decision making units (DMU). Many investigations have dealt with the DEA models, but few have focused on heterogeneous DMUs, outlier detection, and scalability over large data sets. 

In this book, a comprehensive model is presented. A constraint based clustering method is introduced for early detection of outliers to evaluate the performance scores of non homogeneous DMUs. The book includes the different preprocessing stages used in applying different approaches of data mining. 

Along with the theory, an extensive analysis in assessing the transportation system funding for school districts in the state of North Dakota is provided. This book is originally a Ph.D. dissertation at NDSU,Fargo, ND, USA.