Institutional Research and Planning: Its Role in Higher Education Decision Support and Policy Development

Author(s):  
Karen L. Webber ◽  
Angel J. Calderon
2020 ◽  
Vol 4 (1) ◽  
pp. 36
Author(s):  
Arief Budiman ◽  
Yuyun Dwi Lestari ◽  
Yessi Fitri Annisah Lubis

<p>Banyaknya Perguruan Tinggi khususnya di kota Medan dengan menawarkan kelebihan masing-masing mulai dari akreditas, fasilitas dan lain sebagainya, membuat calon mahasiswa bingung untuk memilih Perguruan Tinggi terbaik di kota Medan. Untuk  dapat memilih Perguruan Tinggi calon mahasiswa melakukan survey terlebih dahulu tentang informasi masing-masing Perguruan Tinggi yang khsususnya berada di kota Medan. Dengan menggunakan Sistem Pendukung Keputusan maka sebuah permasalahan dapat mudah teratasi dengan cepat khususnya mengenai pemilihan dalam menentukan Perguruan Tinggi terbaik di kota Medan. Dalam penelitian ini Sistem Pendukung Keputusan yang dibuat menggunakan metode Simple Additive Weighting. SAW lebih efisien karena waktu yang dibutuhkan dalam perhitungan lebih singkat.</p><p> </p><p><strong>Kata Kunci</strong> :<em>Perguruan Tinggi, Sistem Pendukung Keputusan, Metode SAW</em></p><p> </p><p align="center"> </p><p align="center"><em>Abstract</em></p><p><em>The number of universities, especially in the city of Medan by offering their respective advantages ranging from accreditation, facilities, etc., makes prospective students confused to choose the best university in the city of Medan. To be able to choose a university prospective students do a survey in advance about the information of each university which is specifically located in the city of Medan. By using a Decision Support System, a problem can be easily resolved quickly, especially regarding the election in determining the best university in the city of Medan. In this study a Decision Support System was made using the Simple Additive Weighting method. SAW is more efficient because the time needed in calculations is shorter.</em><em><br /> <br /> Keywords: Higher Education, Decision Support System, SAW Method</em></p>


2017 ◽  
Vol 2 (1) ◽  
pp. 240-248 ◽  
Author(s):  
Vassilis Kostoglou ◽  
Konstantinos Kafkas

Abstract This work is an attempt to contribute to the knowledge and guidance of young people (lyceum graduates, higher education students and recent graduates) regarding important issues related to their career and vocational prospects. These issues are related to major relevant questions such as 'what' and 'where' to study, as well as the contents and the prospects of all provided specializations by the departments of Greek institutes of higher education. This article focuses on the analysis and the design of a mobile-based decision support system (DSS) to assist its users in getting thoroughly informed about HE studies in Greece, and eventually in choosing their vocational prospects. An extensive literature and applications review has revealed that there are no such DDS systems, giving to this work an innovative character. The article contains all main elements of system's architecture and design including the essential technical information, presents the main features and representative screenshots of the mobile-based application and comes to conclusions and future suggested work.


Author(s):  
Noerlina ◽  
Siti Elda Hiererra ◽  
Bahtiar Saleh Abbas ◽  
Brilly Andro Makalew ◽  
Desi Maya Kristin ◽  
...  

2016 ◽  
Vol 12 (1) ◽  
pp. 201
Author(s):  
Bilal Mohammed Salem Al-Momani

Decision support systems (DSS) are interactive computer-based systems that provide information, modeling, and manipulation of data. DSS are clearly knowledge-based information systems to capture, Processing and analysis of information affecting or aims to influence the decision making process, performed by people in scope professional job appointed by a user. Hence, this study describes briefly the key concepts of decision support systems such as perceived factors with a focus on quality  of information systems and quality of information variables, behavioral intention of using DSS, and actual DSS use by adopting and extending the technology acceptance model (TAM) of Davis (1989); and Davis, Bagozzi and Warshaw (1989).There are two main goals, which stimulate the study. The first goal is to combine Perceived DSS factors and behavioral intention to use DSS from both the social perspective and a technology perspective with regard to actual DSS usage, and an experimental test of relations provide strategic locations to organizations and providing indicators that should help them manage their DSS effectiveness. Managers face the dilemma in choosing and focusing on most important factors which contributing to the positive behavioral intention of use DSS by the decision makers, which, in turn, could contribute positively in the actual DSS usage by them and other users to effectively solve organizational problems. Hence, this study presents a model which should provide the useful tool for top management in the higher education institutions- in particular-to understand the factors that determine using behaviors for designing proactive interventions and to motivate the acceptance of TAM in order to use the DSS in a way that contributes to the higher education decision-making plan and IT policy.To accomplish or attain the above mentioned objectives, the researcher developed a research instrument (questionnaire) and distributed it amongst the higher education institutions in Jordan to collect data in order to empirically study hypothesis testing (related to the objectives of study). 341 questionnaires were returned from the study respondents. Data were analyzed by utilizing both SPSS (conducted descriptive analysis) and AMOS (conducting structural equation modelling).Findings of the study indicate that some hypotheses were supported while the others were not. Contributions of the study were presented. In addition, the researcher presented some recommendations. Finally, this study has identified opportunities for further study which has progressed greatly advanced understanding constantly of DSS usage, that can help formulate powerful strategies Involving differentiation between DSS perceived factors.


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