Abstract
Measurement of the efficiency of the university performance. Data Envelopment Analysis (DEA) is a data-based performance evaluation method used when multiple inputs and outputs are represented in the Decision-Making Unit (DMU) set. In DEA, when there is a value of Non-Zero Input and Output Slacks then this often means inefficiency. This scalar measure directly with the input of surplus and the output of the short decision of the decision-making unit (DMU). DEA Structure usually apply in general settings, actually DMUs can fall into distinct groups whose members experience similar circumstances. The targets of the Ministry of Research, Technology and Higher Education of the Republic of Indonesia (KEMENRISTEKDIKTI), one of which is the measurement of the efficiency based on the number of lecturers' research, the efficient use of resources. This study will group each department at the Universitas Malikussaleh using the Group Common Benchmarking approach and then provide suggestions for improvements to each group by using Slack-Based Measures.
Highlights
Data Envelopment Analysis (DEA) is an optimization framework proposed to measure the relative performance of a set of Decision Making Units (DMUs) [1]
In the DEA Method, we can identify the Efficient Frontier based on a certain subset of efficient DMU, which can be viewed as a common reference set and will minimize the paretoefficient frontier [7]
The Common Group Benchmarking can be used to determine the minimum value of each input and the inefficient output to the paretto efficient frontier value so that it can be used as a basis for using slack based measure
Summary
Data Envelopment Analysis (DEA) is an optimization framework proposed to measure the relative performance of a set of Decision Making Units (DMUs) [1]. In the DEA Method, we can identify the Efficient Frontier based on a certain subset of efficient DMU, which can be viewed as a common reference set and will minimize the paretoefficient frontier [7]. From this new efficient frontier this will find the closest targets to each of DMU [8]. In grouping based on efficient frontier it is necessary to pay attention to the quality of grouping [9] and need to pay
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