Fuzzy multicriteria model to support decision making during the selection process of teaching and research staff in higher education

2021 ◽  
Author(s):  
Ivana Tadić ◽  
Branka Marasović ◽  
Ivana Jerković
Keyword(s):  
Higher Education ◽  
Decision Making ◽  
Selection Process ◽  
Research Staff ◽  
Teaching And Research ◽  
Multicriteria Model ◽  
Support Decision Making

Evaluation of the Academic Setting in Spain 1This study was financed by the University of Oviedo.

1995 ◽  
Vol 11 (2) ◽  
pp. 133-137 ◽  
Author(s):  
Juan Fernández ◽  
Miguel A. Mateo ◽  
José Muñiz
Keyword(s):  
Higher Education ◽  
Decision Making ◽  
Social Climate ◽  
Three Dimensions ◽  
Academic Setting ◽  
Teaching And Research ◽  
Evaluation Questionnaire ◽  
University Teachers ◽  
The University

The conditions are investigated in which Spanish university teachers carry out their teaching and research functions. 655 teachers from the University of Oviedo took part in this study by completing the Academic Setting Evaluation Questionnaire (ASEQ). Of the three dimensions assessed in the ASEQ, Satisfaction received the lowest ratings, Social Climate was rated higher, and Relations with students was rated the highest. These results are similar to those found in two studies carried out in the academic years 1986/87 and 1989/90. Their relevance for higher education is twofold because these data can be used as a complement of those obtained by means of students' opinions, and the crossing of both types of data can facilitate decision making in order to improve the quality of the work (teaching and research) of the university institutions.

scholarly journals Sistem Pendukung Keputusan Pemilihan Tenaga Kerja Indonesia (TKI) Berdasarkan Kualitas Untuk Menentukan Tempat Kerja Menggunakan Metode Profile Matching (Studi Kasus: PT Adila Prezkifarindo Duta)

2020 ◽  
Vol 1 (2) ◽  
pp. 142
Author(s):  
Dasarius Gulo
Keyword(s):  
Decision Making ◽  
Migrant Workers ◽  
Selection Process ◽  
Matching Method ◽  
Matching Process ◽  
Profile Matching ◽  
Long Time ◽  
Support Decision Making ◽  
Selection Of ◽  
The Ideal

In the process of selecting Indonesian Workers (TKI) based on quality at PT. Adila Prezkifarindo Duta is classified as still manual, where there is not yet a system for selecting quality migrant workers so it requires a long time for its assessment and the selection process is less effective. To support decision making in the selection of qualified Indonesian Workers (TKI) to make it easier by using a decision support system. One method used in the selection of qualified Indonesian Workers is the Profile Matching method. The profile matching method is a decision-making mechanism by assuming that there is an ideal level of predictor variables that must be met by applicants, rather than the minimum level that must be met or passed. In the profile matching process a process will be compared between individual competencies into standard competencies so that different competencies can be identified (also called Gap). The smaller the gap produced, the greater the weight value. In matching this profile, the selected TKI candidates are Indonesian Workers who are closest to the ideal profile of a qualified TKI.

scholarly journals Higher education and oil: The cost of credit and crude – A strategic corollary for industry and higher education

2020 ◽  
pp. 095042222095954
Author(s):  
Joseph M. Woodside
Keyword(s):  
Higher Education ◽  
Decision Making ◽  
Policy Development ◽  
Oil Industry ◽  
Organizational Outcomes ◽  
Lessons Learned ◽  
Cycle Model ◽  
Business Cycle Model ◽  
The Cost ◽  
Support Decision Making

The market shock that accompanied COVID-19 has the potential to significantly transform higher education. At the same time, it presents an opportunity for higher education to learn from industry and adopt successful policies and practices. This paper provides lessons learned from the oil industry which may help higher education institutions to successfully navigate disruption and improve organizational outcomes. A four-phase business cycle model is presented as a strategic corollary for industry and higher education to support decision-making and provide a mechanism for discussion and policy development.

scholarly journals IMPLEMENTASI STAR SCHEMA PADA STUDI KASUS PERPUSTAKAAN BERSKALA UNIVERSITAS

2021 ◽  
Vol 4 (1) ◽  
pp. 1-11
Author(s):  
Wildan Suharso ◽  
Abims Fardiansa ◽  
Yuda Munarko ◽  
Hardianto Wibowo
Keyword(s):  
Decision Making ◽  
Selection Process ◽  
Complex Problem ◽  
The Other ◽  
Item Selection ◽  
Fully Integrated ◽  
Star Schema ◽  
Storage Complexity ◽  
High Storage ◽  
Support Decision Making

Libraries are service units with high storage complexity as evidenced by more data being stored for each year. The data that is not integrated makes the complex problem because every year the process that is carried out continues to increase, especially for the circulation of loans. As the number of books increases, the circulation of borrowing increases every year. On the other hand, the library must know exactly what collection of books they have and the transactions it has made. A lot of data is owned by the library cannot be utilized optimally, so that the managerial is unable to make full use of the data. In University scale libraries, this problem increases when the data is not fully integrated. In this study, the implementation of a star schema was carried out to solve problems related to data integration using a nine-step methodology, which includes selection, item selection, process dimensions, fact selection, fact storage, ensuring dimension tables, selecting database duration, changing dimensions, determining priorities, and query models. The results of this study indicate that the star schema can be implemented in the case of libraries, data warehouses and OLAP to support decision making for adding books, and produced 3 dimensions of the 4 grains found.  

scholarly journals Implemetasi Data Warehouse pada Bagian Pemasaran Perguruan Tinggi

2012 ◽  
Vol 3 (1) ◽  
pp. 315
Author(s):  
Eka Miranda ◽  
Rudy Rudy ◽  
Eli Suryani
Keyword(s):  
Higher Education ◽  
Decision Making ◽  
Data Warehouse ◽  
Ad Hoc ◽  
External Data ◽  
Study Results ◽  
Marketing Activities ◽  
Warehouse Design ◽  
Transactional Data ◽  
Support Decision Making

Transactional data are widely owned by higher education institutes, but the utilization of the data to support decision making has not functioned maximally. Therefore, higher education institutes need analysis tools to maximize decision making processes. Based on the issue, then data warehouse design was created to: (1) store large-amount data; (2) potentially gain new perspectives of distributed data; (3) provide reports and answers to users’ ad hoc questions; (4) perform data analysis of external conditions and transactional data from the marketing activities of universities, since marketing is one supporting field as well as the cutting edge of higher education institutes. The methods used to design and implement data warehouse are analysis of records related to the marketing activities of higher education institutes and data warehouse design. This study results in a data warehouse design and its implementation to analyze the external data and transactional data from the marketing activities of universities to support decision making.

Governments Need To, and Do, Trust Universities

2019 ◽  
pp. 385-393
Author(s):  
Mike B. Calford
Keyword(s):  
Higher Education ◽  
Decision Making ◽  
Teaching And Research ◽  
Distributed Decision Making ◽  
University Systems ◽  
Direct Support ◽  
Almost All ◽  
Distributed Decision ◽  
Multiple Jurisdictions

Through direct support funding, granting agencies, student scholarships, tax concessions, and other sources governments provide the vast bulk of funding to operate universities. However, governments cede control of how those funds are used to the universities, and these cede control of curricula, assessment, and standards to their academics. Why is this the case for almost all successful university systems? The usual explanation, that the best outcomes of academic pursuit occur with distributed decision making, is simply another description of what has been common in successful systems of higher education under multiple jurisdictions. An answer may come from the consideration that, typically, governments and universities operate on very different timescales. The academic cycles for teaching and research (ten to twenty-five years) far exceed the span of most government administrations (three to five years).

scholarly journals Penerapan Algoritma C4.5 untuk Seleksi Penerimaan Siswa Baru pada SD Islam Terpadu Permata Bunda Demak Implementation of Decision Tree Algorithm for Selection of New Student Admission on Permata Bunda Integrated Islamic Elementary School

CCIT Journal ◽  
2018 ◽  
Vol 11 (2) ◽  
pp. 158-170
Author(s):  
Linda Monizah Fitriani ◽  
Andik Setyono
Keyword(s):  
Decision Making ◽  
Decision Tree ◽  
Selection Process ◽  
Application Form ◽  
Assessment Tests ◽  
Data Mining Approach ◽  
C4.5 Decision Tree ◽  
New Students ◽  
Screening Assessment ◽  
Support Decision Making

The new admission process of selection is a basic rules for determining studying and learning in schools. This process requires precision so that the results are accurate and precise. The selection process for new students are divided into two types of screening, assessment tests and interviews. The purpose of this study is to assist schools in selecting prospective students so that they can be a decision support for new students. Thus, the need for data mining approach to generate information that can support decision-making for new admissions. The algorithm used is a C4.5 decision tree. C4.5 algorithms can support decision making new admissions through the rules generated. The testing process with RapidMiner yield 90.50% accuracy. Based on these tests, the researchers reprocess into the application form to help the school. So, do the questionnaire to the school to investigate the role of applications in the form of 10 questions by 20 teachers and an index of 81.5%. Thus, schools are satisfied with the application and can help the selection process by the school

The University of Panic

2022 ◽  
pp. 277-289
Author(s):  
Tara Brabazon
Keyword(s):  
Higher Education ◽  
Decision Making ◽  
Online Learning ◽  
Teaching And Learning ◽  
Social Problems ◽  
Education Students ◽  
Teaching And Research ◽  
Paul Virilio ◽  
Public Scrutiny ◽  
The University

A pandemic crushes assumptions and inherited narratives of higher education. This chapter explores how COVID-19 tested the parameters of teaching and learning and how universities failed this test. Through the panic of shutdowns, lockdowns, economic restructures, social distancing, and closures, the speed of change and decision making was profound and under public scrutiny. Online learning has been a panacea for economic and social problems for 20 years. To manage a crisis the scale of COVID-19, online learning would be the obvious solution. However, the pandemic showed the flaws in this strategy and the toxic reality of quick fixes to higher education. Students were short changed and academics pushed to exhaustion. After COVID-19, higher education is in shreds. The visions and futures of universities are blurred. Using the theories of Paul Virilio, particularly his University of Disaster, this chapter probes how higher education unravels and dissociates teaching and research. When time is short and risks are high, what mode of leadership will survive in the post-pandemic university?

scholarly journals Organizational Culture in Higher Education: Learning from the Best

2016 ◽  
Vol 6 (1) ◽  
pp. 135 ◽  
Author(s):  
Adela Coman ◽  
Catalina Bonciu
Keyword(s):  
Higher Education ◽  
Decision Making ◽  
Organizational Culture ◽  
Higher Education Institutions ◽  
Education Institution ◽  
Harvard University ◽  
Comparative Perspective ◽  
Teaching And Research ◽  
Decision Making Processes ◽  
The University

In this paper we discuss organizational culture of higher education institutions whose components have been thoroughly described by authors such as Tierney (1988) and Valimaa (1998). We focused on the elements of organizational culture which outlines the identity of a higher education institution: why does the institution exist? How does the institution reach its goals and mission? What does the institution offer to its internal and external public? As such, we analyzed the mission, structure, governance and decision making processes, teaching and research in a comparative perspective: Harvard University (HU) and the University of Bucharest (UB), Romania. By looking into the organizational culture of the best, we learnt some lessons that may inspire, motivate and urge action if UB wants to progress so as to become one day a top leader in higher education worldwide.

scholarly journals Multicriteria Model Proposition to Support the Management of Systems of E-Waste Collection

Logistics ◽  
2021 ◽  
Vol 5 (3) ◽  
pp. 60
Author(s):  
Ciro Henrique de Araújo Fernandes ◽  
Lucio Camara e Silva ◽  
Patricia Guarnieri ◽  
Bárbara de Oliveira Vieira
Keyword(s):  
Decision Making ◽  
Environmental Sustainability ◽  
Electronic Waste ◽  
Multicriteria Decision Making ◽  
Public Agency ◽  
Proposed Model ◽  
Global Concern ◽  
Support Policy ◽  
Multicriteria Model ◽  
Support Decision Making

Background: Considering the global concern in balancing economic growth with environmental sustainability, the study proposes a model to support multicriteria decision-making. From the systematic literature review and bibliometric analysis, there was an increasing trend in studies on electronic waste due to governments, stakeholders, and the population to better address the management of this waste; Methods: We propose a decision model considering some aspects and phases that help from collecting information to support decision making, based on the FITradeoff ordering method, to support policy decisions for managing Waste from Electrical and Electronic Equipment (WEEE) collection systems.; Results: After applying the proposed model, validated based on the perception of a decision-maker working in a federal public agency, we obtained the final classification with ten positions of alternatives; Conclusions: This outcome can assist in decision making and management of the collection of WEEE. In addition, we made recommendations to manufacturers have more responsibility in the design and traceability of the product to guarantee its recovery after disposal effectively.

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