Sustainable Performance Measurement of Automotive and Machinary Industrial Cluster based of Industrial Symbiosis Scenario in the Industrial Estate

  • Authors

    • Ahmad Mubin
    • . .
    2019-01-26
    https://doi.org/10.14419/ijet.v8i1.9.26386
  • Industrial Estate, Industrial Symbiosis, OMAX, SBSC-L, Sustainability Performance

  • Abstract

    Sustainability issues become a remarkable study lately, including the industrial sustainability, it is in line with the long term of industrial development goal to build industry according to sustainable development concept. This research aims to design a sustainability performance measurement system of automotive and machinery industrial cluster with the approach of Sustainability Balanced Scorecard and Labuschagne (SBSC-L) model, and to measure and evaluate the sustainability performance of the industry using Objective Matrix (OMAX) and Traffic Light System methods. Results of measurement and evaluation of the overall sustainability performance on scenario 0 are obtained that industry P is 4.43 (yellow) which means good, industry Q is 3.38 (red) which means poor, and industry R is 4.74 (yellow) that means good or satisfactory, industry R has the highest value of sustainability performance, and average of sustainability performance is 4.25. The application of industrial symbiosis scenario provides improved sustainability performance on average in scenario I by 68%, scenario II by 81%, and scenario III by 96% compared to scenario 0. Thus, it needs the policy for encouraging the application of industrial symbiosis systems in order to improve the sustainability performance of the industry in the industrial estate.

     

  • References

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  • How to Cite

    Mubin, A., & ., . (2019). Sustainable Performance Measurement of Automotive and Machinary Industrial Cluster based of Industrial Symbiosis Scenario in the Industrial Estate. International Journal of Engineering & Technology, 8(1.9), 136-138. https://doi.org/10.14419/ijet.v8i1.9.26386

    Received date: 2019-01-22

    Accepted date: 2019-01-22

    Published date: 2019-01-26