Enhancing sustainability index parameter using ANFIS computational intelligence model
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 foll...
Saved in:
Main Authors: | , , , , |
---|---|
Format: | Article |
Language: | English English |
Published: |
Kulliyah of Engineering, International Islamic University Malaysia
2023
|
Subjects: | |
Online Access: | http://irep.iium.edu.my/105598/7/105598_Enhancing%20sustainability%20index%20parameter%20using%20ANFIS%20computational.pdf http://irep.iium.edu.my/105598/13/105598_Enhancing%20sustainability%20index%20parameter%20using%20ANFIS%20computational%20intelligence%20model_Scopus.pdf http://irep.iium.edu.my/105598/ https://journals.iium.edu.my/ejournal/index.php/iiumej/article/view/2810/933 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Universiti Islam Antarabangsa Malaysia |
Language: | English English |
id |
my.iium.irep.105598 |
---|---|
record_format |
dspace |
spelling |
my.iium.irep.1055982024-01-31T04:12:51Z http://irep.iium.edu.my/105598/ Enhancing sustainability index parameter using ANFIS computational intelligence model Septiyana, Diah Abd. Rahman, Mohamed Mohamed Ariff, Tasnim Firdaus Sukindar, Nor Aiman Triblas Adesta, Erry Yulian T175 Industrial research. Research and development 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. Kulliyah of Engineering, International Islamic University Malaysia 2023-07-04 Article PeerReviewed application/pdf en http://irep.iium.edu.my/105598/7/105598_Enhancing%20sustainability%20index%20parameter%20using%20ANFIS%20computational.pdf application/pdf en http://irep.iium.edu.my/105598/13/105598_Enhancing%20sustainability%20index%20parameter%20using%20ANFIS%20computational%20intelligence%20model_Scopus.pdf 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 https://journals.iium.edu.my/ejournal/index.php/iiumej/article/view/2810/933 10.31436/iiumej.v24i2.2810 |
institution |
Universiti Islam Antarabangsa Malaysia |
building |
IIUM Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
International Islamic University Malaysia |
content_source |
IIUM Repository (IREP) |
url_provider |
http://irep.iium.edu.my/ |
language |
English English |
topic |
T175 Industrial research. Research and development |
spellingShingle |
T175 Industrial research. Research and development Septiyana, Diah Abd. Rahman, Mohamed Mohamed Ariff, Tasnim Firdaus Sukindar, Nor Aiman Triblas Adesta, Erry Yulian Enhancing sustainability index parameter using ANFIS computational intelligence model |
description |
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. |
format |
Article |
author |
Septiyana, Diah Abd. Rahman, Mohamed Mohamed Ariff, Tasnim Firdaus Sukindar, Nor Aiman Triblas Adesta, Erry Yulian |
author_facet |
Septiyana, Diah Abd. Rahman, Mohamed Mohamed Ariff, Tasnim Firdaus Sukindar, Nor Aiman Triblas Adesta, Erry Yulian |
author_sort |
Septiyana, Diah |
title |
Enhancing sustainability index parameter using ANFIS computational intelligence model |
title_short |
Enhancing sustainability index parameter using ANFIS computational intelligence model |
title_full |
Enhancing sustainability index parameter using ANFIS computational intelligence model |
title_fullStr |
Enhancing sustainability index parameter using ANFIS computational intelligence model |
title_full_unstemmed |
Enhancing sustainability index parameter using ANFIS computational intelligence model |
title_sort |
enhancing sustainability index parameter using anfis computational intelligence model |
publisher |
Kulliyah of Engineering, International Islamic University Malaysia |
publishDate |
2023 |
url |
http://irep.iium.edu.my/105598/7/105598_Enhancing%20sustainability%20index%20parameter%20using%20ANFIS%20computational.pdf http://irep.iium.edu.my/105598/13/105598_Enhancing%20sustainability%20index%20parameter%20using%20ANFIS%20computational%20intelligence%20model_Scopus.pdf http://irep.iium.edu.my/105598/ https://journals.iium.edu.my/ejournal/index.php/iiumej/article/view/2810/933 |
_version_ |
1789940144949690368 |