College Ranking Analysis Using VIKOR Method

College ranking is the main thing used as a basis to attract prospective new students. Prospective new students will generally look for related information from which universities are the best to choose in the future. In the ranking of universities based on the official page of the Ministry of Research, Technology and Higher Education, the ranking of universities, both public and private, can be a reference for recruiting prospective students. The better the college ranking, the more attractive prospective new students are. To determine the ranking of a university, a decision support system is needed. There are many methods available from the decision support system, but in this study, the author will use the VIKOR method (Visekriterijumsko Kompromisno Rangiranje), which is part of the MCDM (Multi-Criteria Decision Making), as a solution to these problems. The VIKOR method is a multi-criteria optimization method that can be used on fairly complex systems. In this study, the sample data used came from 10 universities in the city of Medan, where the initials of each naming were colleges A to J. From the results of research analysis using the VIKOR method, the ranking results were as follows, where college B got the first rank with the lowest score of 0. Then the second rank was college G and in the third rank was college H with each score of 0.248211396 and 0.304702661. For the fourth, fifth, sixth, seventh to tenth ranks, they are sorted from colleges A, I, C, E, F, D, and J.

Universities of the Muslim World in Context of Globalization

This article expects to discourse the fundamental matters in regard to the emergency in advanced education in Muslim nations and investigate conceivable pathways for change. Notwithstanding being tested by the developing hole in instructive guidelines and accomplishments between exceedingly industrialized countries and Muslim nations, most Muslim social orders keep on producing fair outcome in advanced education. It’s clear in most recent world college ranking, advance significance to evaluate the effect and difficulties of globalization on advanced education in Muslim social orders addressed in this article and additionally the main drivers of the emergency of advanced education in Muslim social orders, bad administration and insufficient governmental strategies lie at the base of the emergency.

An empirical evaluation of Chinese college admissions reforms through a natural experiment

College admissions policies affect the educational experiences and labor market outcomes for millions of students each year. In China alone, 10 million high school seniors participate in the National College Entrance Examination to compete for 7 million seats at various universities each year, making this system the largest centralized matching market in the world. The last 20 y have witnessed radical reforms in the Chinese college admissions system, with many provinces moving from a sequential (immediate acceptance) mechanism to some version of the parallel college admissions mechanism, a hybrid between the immediate and deferred acceptance mechanisms. In this study, we use a natural experiment to evaluate the effectiveness of the sequential and parallel mechanisms in motivating student college ranking strategies and providing stable matching outcomes. Using a unique dataset from a province that implemented a partial reform between 2008 and 2009, we find that students list more colleges in their rank-ordered lists, and more prestigious colleges as their top choices, after the province adopts the parallel mechanism in its tier 1 college admissions process. These listing strategies in turn lead to greater stability in matching outcomes, consistent with our theoretical prediction that the parallel mechanism is less manipulable and more stable than the sequential mechanism.

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 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.

Ranking games

This chapter starts with a discussion of the magic power of round numbers and left-digit effects, and it then deals with two popular ranking games concerning colleges and countries. A recurring theme in our complex world pertains to the question of whether it is possible to summarize the performance of an organization faithfully with a single score. Schools are complex social organizations that serve a variety of purposes, and measuring their progress toward these goals is obviously tricky. Students, admissions offices, and college administrators are the major stakeholders in the college ranking game. Ranking colleges not only provides a passive mirror of the institutional landscape but also drives changes within the institutions. Similarly, ranking countries both reflects the current state and motivates change. While some believe that the idea of the nation-state is outdated and a source of conflict, countries remain a primary means of controlling people, organizing society, and managing the distribution of wealth. Measuring corruption and freedom within countries is difficult, and the ranking of countries based on these measurements is discussed.

Ranking

As humans, we like to see who is stronger, richer, better, or cleverer. As we also (1) love lists, (2) are competitive, and (3) are jealous of other people, we like ranking. We can rank some situations objectively: students ranked by their heights reflects objectivity. However, many “top-10” (or 21, 33, etc.) lists are based on subjective categorization and give only the illusion of objectivity. In fact, we don’t always want to be seen objectively since we don’t mind having a better image or rank than we deserve. The book applies scientific theories to everyday experience by raising and answering questions like: Are college ranking lists objective? How do we rank and rate countries based on their fragility, level of corruption, or even happiness? How do we find the most relevant webpages? How are employees ranked? The book is offered to people whose neighbor has a fancier car; employees who are being ranked by their supervisors; managers who are involved in ranking but may have qualms about the process; businesspeople interested in creating better visibility for their companies; scientists, writers, artists, and other competitors who would like to see themselves at the top of a success list; and college students who are just preparing to enter a new phase of social competition. Readers will engage in an intellectual adventure to better understand the difficulties of navigating between objectivity and subjectivity and to better identify and modify their place in real and virtual communities by combining human and computational intelligence.