DEA Optimization with Neural Network in Benchmarking Process

The object of research that will be examined in this study is the problem of benchmarking by using Data Envelopment Analysis (DEA). The result of benchmarking obtained through the DEA method in the form of benchmarking values should be studies as a pattern when there is a new data can be directly predicted. On this side required a well-known application of Artificial Neural Networks in studying existing patterns. The results of this study are in the form of optimization is performed on DEA method to guarantee the principle of quality assurance in detecting early the quality of a new pattern emerging. Based on the result of the research, we can predict emerging new patterns that become in efficient.