Analysis of Multi-attribute Utility Theory for College Ranking Decision Making

Ranking of a tertiary institution, both state and private universities, can be the basis of the tertiary institutions of interest to prospective new students. The better the ranking of the college, the more popular the campus. In this study the author discusses the case of campus ranking in the city...

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Main Authors: Adidtya Perdana, Arief Budiman
Format: Article
Language:English
Published: Politeknik Ganesha Medan 2020-03-01
Series:Sinkron
Online Access:https://jurnal.polgan.ac.id/index.php/sinkron/article/view/10232
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spelling doaj-c314de8501a14927817c576f78462e082020-11-25T03:28:27ZengPoliteknik Ganesha MedanSinkron2541-044X2541-20192020-03-0142192610.33395/sinkron.v4i2.1023210232Analysis of Multi-attribute Utility Theory for College Ranking Decision MakingAdidtya Perdana0Arief BudimanUniversitas Harapan MedanRanking of a tertiary institution, both state and private universities, can be the basis of the tertiary institutions of interest to prospective new students. The better the ranking of the college, the more popular the campus. In this study the author discusses the case of campus ranking in the city of Medan where the results to be received are the best campus decision making with the method used is the MAUT (Multi Attribute Utility Theory) method. The aim is to see what results can be given by using the MAUT method in determining the best campus in the city of Medan which results in ranking the campus in Medan. Does it provide optimal results or not. But every case that is solved using the methods in artificial intelligence, in this case the MAUT method is a method of the Decision Support System, certainly provides optimal results even though the results given are not complete or complete. Therefore, the writer has a vision going forward, conducting research in this field, especially for the case of campus ranking. In this study the variables used in determining campus ranking are Institutional, Student Activities, Lecturer HR, Research and Community Service, and Innovation. These five variables in the future can be added or subtracted as needed. The results obtained are optimal ranking results but are still limited to the reference model for internal institutions.https://jurnal.polgan.ac.id/index.php/sinkron/article/view/10232
collection DOAJ
language English
format Article
sources DOAJ
author Adidtya Perdana
Arief Budiman
spellingShingle Adidtya Perdana
Arief Budiman
Analysis of Multi-attribute Utility Theory for College Ranking Decision Making
Sinkron
author_facet Adidtya Perdana
Arief Budiman
author_sort Adidtya Perdana
title Analysis of Multi-attribute Utility Theory for College Ranking Decision Making
title_short Analysis of Multi-attribute Utility Theory for College Ranking Decision Making
title_full Analysis of Multi-attribute Utility Theory for College Ranking Decision Making
title_fullStr Analysis of Multi-attribute Utility Theory for College Ranking Decision Making
title_full_unstemmed Analysis of Multi-attribute Utility Theory for College Ranking Decision Making
title_sort analysis of multi-attribute utility theory for college ranking decision making
publisher Politeknik Ganesha Medan
series Sinkron
issn 2541-044X
2541-2019
publishDate 2020-03-01
description Ranking of a tertiary institution, both state and private universities, can be the basis of the tertiary institutions of interest to prospective new students. The better the ranking of the college, the more popular the campus. In this study the author discusses the case of campus ranking in the city of Medan where the results to be received are the best campus decision making with the method used is the MAUT (Multi Attribute Utility Theory) method. The aim is to see what results can be given by using the MAUT method in determining the best campus in the city of Medan which results in ranking the campus in Medan. Does it provide optimal results or not. But every case that is solved using the methods in artificial intelligence, in this case the MAUT method is a method of the Decision Support System, certainly provides optimal results even though the results given are not complete or complete. Therefore, the writer has a vision going forward, conducting research in this field, especially for the case of campus ranking. In this study the variables used in determining campus ranking are Institutional, Student Activities, Lecturer HR, Research and Community Service, and Innovation. These five variables in the future can be added or subtracted as needed. The results obtained are optimal ranking results but are still limited to the reference model for internal institutions.
url https://jurnal.polgan.ac.id/index.php/sinkron/article/view/10232
work_keys_str_mv AT adidtyaperdana analysisofmultiattributeutilitytheoryforcollegerankingdecisionmaking
AT ariefbudiman analysisofmultiattributeutilitytheoryforcollegerankingdecisionmaking
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