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Enhancing sustainability index parameter using ANFIS computational intelligence model

Septiyana, Diah and Abd. Rahman, Mohamed and Mohamed Ariff, Tasnim Firdaus and Sukindar, Nor Aiman and Triblas Adesta, Erry Yulian (2023) Enhancing sustainability index parameter using ANFIS computational intelligence model. IIUM Engineering Journal, 24 (2). pp. 258-268. ISSN 1511-788X E-ISSN 2289-7860

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The scarcity of water resource is an essential global issue in the 21st century. Therefore, one of the Sustainable Development Goals (SDG) was to ensure the availability and sustainable management of water and sanitation. To do this, it is necessary to assess whether or not the SDG has been followed using the sustainability index. However, there are a lot of sustainability indexes and many of them have the same problem, in which all sustainability index parameters have the same weightage. This problem shows us that every parameter in the sustainability index is equal, while in real life there is no equal parameter. In this paper a weightage for each parameter is proposed to enhance the sustainability index. The method to assess the sustainability index parameters was using a questionnaire by key experts in the water industry. Using ANFIS computational intelligence, the result of the assessment was then fit to the frequent parameters that exist in other sustainability indexes. This proposed method can produce a ranking and weight for each sustainability index parameter and criteria. Using this method, the weightage for each sustainability index parameter can be generated,such as environmental 0.301, engineering 0.214, economic 0.280, and social 0.205.

Item Type: Article (Journal)
Uncontrolled Keywords: Sustainability Index, Computational Intelligence, ANFIS, Weightage, Water Industry
Subjects: T Technology > T Technology (General) > T175 Industrial research. Research and development
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering
Kulliyyah of Engineering > Department of Manufacturing and Materials Engineering
Depositing User: Dr NOR AIMAN SUKINDAR
Date Deposited: 18 Jul 2023 08:41
Last Modified: 31 Jan 2024 12:12
URI: http://irep.iium.edu.my/id/eprint/105598

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