Efficiency of Environmental Performance Measurement Using Data Envelopment Analysis (DEA) With Fuzzy Approach

English

Authors

DOI:

https://doi.org/10.32734/jormtt.v7i2.21717

Abstract

This study aims to analyze and measure environmental performance efficiency in residential areas in Medan City using the Data Envelopment Analysis (DEA) method combined with a fuzzy approach. Environmental performance is measured based on relevant inputs and outputs, where the data used are secondary data obtained from previous research reports. Fuzzification is applied to address uncertainty in the data by converting input and output values into Triangular Fuzzy Numbers (TFN). The results of the study show that out of the 4 Decision Making Units (DMUs) studied without using the fuzzy approach, only the Helvetia housing complex achieved 100% efficiency. Meanwhile, the efficiency values for Tuntungan, Martubung, and Johor housing estates were 85.92%, 88.69%, and 94.87%, respectively. When the fuzzy approach was applied, the efficiency values of the Johor and Helvetia housing estates reached 100% efficiency, while the Tuntungan and Martubung housing estates had an efficiency of 78.22%, indicating inefficiency. This inefficiency is caused by excessive use of drainage inputs, indicating that these housing complexes are unable to produce environmental outputs commensurate with the inputs used. This study recommends improving the quality and quantity of environmental management and cleanliness, as well as the availability and quality of green spaces, to enhance environmental efficiency in housing. The findings of this study provide important insights into the efficiency of environmental performance measurement and highlight opportunities for improvement in environmental management within housing.

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Published

2025-09-19

How to Cite

[1]
N. Nadhila, Tulus, and Mardiningsih, “Efficiency of Environmental Performance Measurement Using Data Envelopment Analysis (DEA) With Fuzzy Approach: English”, J. of Research in Math. Trends and Tech., vol. 7, no. 2, pp. 65–71, Sep. 2025.