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

Abstract

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.