scholarly journals Analisa Data Penerimaan Siswa Pada Perguruan Tinggi melalui Jalur SNMPTN menggunakan Algoritma Fuzzy C-Means (Studi Kasus : SMAN 5 Kota Bengkulu)

2021 ◽  
Vol 11 (2) ◽  
pp. 104-111
Author(s):  
Aan Herwansah
Keyword(s):  
Higher Education ◽  
Data Analysis ◽  
Sql Server ◽  
Administrative Staff ◽  
Fuzzy C Means ◽  
The Arts ◽  
Admission Data ◽  
Data Grouping ◽  
Fuzzy C Means Algorithm ◽  
Analyze Data

SMA Negeri 5 Bengkulu City is one of State Senior High Schools in Bengkulu City that has been accredited A with a total of 58 educators and 23 administrative staff and employees. In addition, SMA Negeri 5 Bengkulu City has also won many achievements both in academics (graduates of SMA N 5 Bengkulu City are accepted at the best universities in Indonesia through test and non-test pathways) as well as in the fields of science (Olympics), Sports, IMTAQ and the arts for the provincial and national levels. Application of student admissions data in higher education through SNMPTN using Fuzzy C-Means Algorithm at SMA N 5 Bengkulu City is an application that can help analyze data grouping based on student admission data into 3 groups. Data Analysis of Student Admissions in higher education through SNMPTN was made using the Visual Basic.Net programming language and SQL Server 2008 database by applying the Fuzzy C-Means algorithm. This application is able to provide information on the results of the analysis of student admissions at Higher Education through SNMPTN. The more data on student admissions in Higher Education, the more accurate the grouping results. Based on the results of the tests that have been carried out, the Application of Student Admission Data in Higher Education through SNMPTN can provide information on the results of data grouping divided into 3 groups, namely high, medium and low

The Effect of Perceived Organizational Support on Job Performance among Administrative Staff of Newly-Built University in China

2018 ◽  
Vol 1 (3) ◽  
pp. 229-232
Author(s):  
Peng Wan ◽  
Khaliza Binti Saidin
Keyword(s):  
Higher Education ◽  
Data Analysis ◽  
Job Performance ◽  
Organizational Support ◽  
Perceived Organizational Support ◽  
Research Review ◽  
Administrative Staff ◽  
Relevant Research ◽  
Online Questionnaire ◽  
Key Factor

In the context of the popularization of higher education and the emergence of a large number of newly-built universities in China, it is important to improve the job performance of administrative for newly-built university effectiveness and outcomes. According to perceived organizational support (POS) theory and relevant research review, POS is considered to be a key factor in improving job performance. However, there is still some research found that POS could not affect job performance directly and researchers are less concerned about university administrative staff. Therefore, this study aimed to determine the effect of perceived organizational support on job performance among administrative staff of newly-built university in China. An online questionnaire was adopted in the study to collect data, and a total of 426 administrative staff participated in the survey. After data analysis by SPSS, the findings indicated that the level of POS and job performance among administrative staff is slightly low. The findings also revealed that a positive correlation exists between POS and job performance, and the POS has significant effect on job performance. The study further discussed the findings and recommended that more organizational support should be provided by newly-built universities in order to improve the job performance of administrative staff.

Research on the data analysis system of student stress in English MOOC based on fuzzy C-means algorithm

2021 ◽  
pp. 1-11
Author(s):  
Jian Yao ◽  
Lisong Wang ◽  
Ying Liu ◽  
Ying kui
Keyword(s):  
Data Analysis ◽  
Psychological Stress ◽  
Classroom Teaching ◽  
Teaching Process ◽  
Fuzzy C Means ◽  
Student Stress ◽  
Quantitative Identification ◽  
Analysis System ◽  
Data Analysis System ◽  
Fuzzy C Means Algorithm

In order to improve the recognition accuracy of students’ psychological stress data in the English MOOC classroom teaching process, this paper improves the traditional fuzzy C-means algorithm, and uses the deviation value to represent the difference between the average algebraic distance of the neighborhood point and the center pixel. By calculating the deviation value, the influence of the neighborhood point on the center point can be measured, and the noise resistance of the algorithm can be improved. Moreover, this paper constructs a quantitative identification model of student stress data based on the needs of English MOOC teaching stress analysis, and uses image database to verify the basic performance of the algorithm, and constructs a data analysis system of student stress in English MOOC classroom, which is used in practice. In addition, this paper uses student facial expression recognition as a basis for quantitative identification of student stress, and designs experiments to analyze the reliability of the system. From the statistical results, it can be seen that the data analysis system of the students’ psychological stress in the English MOOC classroom teaching process constructed in this paper is effective.

Administrative Environment And Employee Prductivity In Higher Education A Theoritical View

2019 ◽  
Vol 118 (11) ◽  
pp. 230-243
Author(s):  
Jamal Asad Mezel ◽  
Kiran Das Naik Eslavath
Keyword(s):  
Higher Education ◽  
Work Engagement ◽  
Physical Environment ◽  
High Performance ◽  
Educational Institution ◽  
Positive Association ◽  
Faculty Members ◽  
Employee Productivity ◽  
Administrative Staff ◽  
Administrative Employees

Ensure that from the above theoretical review on administrative context and employee productivity in higher education and there is a positive association between work engagement of faculty members and administrative staff motivate the employees in accomplishing their work regardless of any result that they are more productive. Researchers argue the fact that the physical environment of the institutional and administrative, employees effect job perception attitudes and job satisfaction which is in sequence affects the job performance and employee productivity. Improving the work environment in higher educational institution there is a dissatisfaction and complaints of employee while increasing their productivity the more satisfied employee are with their jobs in high performance and productivity.

scholarly journals A News Big Data Analysis of Issues in Higher Education in Korea amid the COVID-19 Pandemic

2021 ◽  
Vol 13 (13) ◽  
pp. 7347
Author(s):  
Jangwan Ko ◽  
Seungsu Paek ◽  
Seoyoon Park ◽  
Jiwoo Park
Keyword(s):  
Higher Education ◽  
Big Data ◽  
Data Analysis ◽  
College Education ◽  
Big Data Analysis ◽  
Second Phase ◽  
Public Attention ◽  
Job Market ◽  
Media Reports ◽  
The Government

This paper examines the main issues regarding higher education in Korea—where college education experienced minimal interruptions—during the COVID-19 pandemic through a big data analysis of news articles. By analyzing policy responses from the government and colleges and examining prominent discourses on higher education, it provides a context for discussing the implications of COVID-19 on education policy and what the post-pandemic era would bring. To this end, we utilized BIgKinds, a big data research solution for news articles offered by the Korea Press Foundation, to select a total of 2636 media reports and conducted Topic Modelling based on LDA algorithms using NetMiner. The analyses are split into three distinct periods of COVID-19 spread in the country. Some notable topics from the first phase are remote class, tuition refund, returning Chinese international students, and normalization of college education. Preparations for the College Scholastic Ability Test (CSAT), contact and contactless classes, preparations for early admissions, and supporting job market candidates are extracted for the second phase. For the third phase, the extracted topics include CSAT and college-specific exams, quarantine on campus, social relations on campus, and support for job market candidates. The results confirmed widespread public attention to the relevant issues but also showed empirically that the measures taken by the government and college administrations to combat COVID-19 had limited visibility among media reports. It is important to note that timely and appropriate responses from the government and colleges have enabled continuation of higher education in some capacity during the pandemic. In addition to the media’s role in reporting issues of public interest, there is also a need for continued research and discussion on higher education amid COVID-19 to help effect actual results from various policy efforts.

scholarly journals Spirals of Sustainable Academic Motivation, Creativity, and Trust of Higher Education Staff

2021 ◽  
Vol 13 (13) ◽  
pp. 7057
Author(s):  
Martina Blašková ◽  
Dominika Tumová ◽  
Rudolf Blaško ◽  
Justyna Majchrzak-Lepczyk
Keyword(s):  
Higher Education ◽  
Academic Motivation ◽  
Slovak Republic ◽  
Point Of View ◽  
Scientific Management ◽  
Administrative Staff ◽  
Sustainable Systems ◽  
New Concepts ◽  
Future Improvement ◽  
The University

Sustainability has to penetrate more and more into higher education. It should not focus only on traditional elements. It should also enter new, but for future improvement, extremely important areas. Based on this premise, creativity and motivation, when additionally interconnected and supported by trust that is provided and achieved, decide on the progress and sustainability of universities. This connection is gaining importance especially from the point of view of building solid foundations and mechanisms that functionally preserve the potential effects of these elements in the future. For this reason and following the nature, importance, and content of sustainable academic motivation (SAM), the paper introduces two new concepts: sustainable academic creativity (SAC) and sustainable academic trust (SAT). For further original contributions, the paper hypothesizes the existence of mutual—spiral—relations of sustainable academic motivation (SAM), sustainable academic creativity (SAC), and sustainable academic trust (SAT). The empirical section tests the validity of this claim in the universities of two countries: the Slovak Republic and Poland. A survey performed on a sample of n=181 pedagogical, scientific, management, and administrative staff in higher education confirms the existence of these spirals. The results indicate the spiral effect of motivation when connected with creativity and trust and show that it is accented by the crucial principles of sustainability (responsibility, novelty, usefulness, progress, etc.). Therefore, the paper’s conclusion contains the explanations for the potential occurrence of three types of sustainably mutual systems and complexes. These are: (a) individual sustainable systems of SAM, SAC, and SAT; (b) group/sectional sustainable systems of SAM, SAC, and SAT; and (c) the global sustainable complex of SAM, SAC, and SAT in the university.

scholarly journals Intuitionistic Fuzzy C-Means Algorithm Based on Membership Information Transfer-Ring and Similarity Measurement

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 696
Author(s):  
Haipeng Chen ◽  
Zeyu Xie ◽  
Yongping Huang ◽  
Di Gai
Keyword(s):  
Brain Tumor ◽  
Information Transfer ◽  
Magnetic Resonance Images ◽  
Low Noise ◽  
Similarity Measurement ◽  
Noise Sensitivity ◽  
Fuzzy C Means ◽  
Intuitionistic Fuzzy ◽  
Membership Information ◽  
Fuzzy C Means Algorithm

The fuzzy C-means clustering (FCM) algorithm is used widely in medical image segmentation and suitable for segmenting brain tumors. Therefore, an intuitionistic fuzzy C-means algorithm based on membership information transferring and similarity measurements (IFCM-MS) is proposed to segment brain tumor magnetic resonance images (MRI) in this paper. The original FCM lacks spatial information, which leads to a high noise sensitivity. To address this issue, the membership information transfer model is adopted to the IFCM-MS. Specifically, neighborhood information and the similarity of adjacent iterations are incorporated into the clustering process. Besides, FCM uses simple distance measurements to calculate the membership degree, which causes an unsatisfactory result. So, a similarity measurement method is designed in the IFCM-MS to improve the membership calculation, in which gray information and distance information are fused adaptively. In addition, the complex structure of the brain results in MRIs with uncertainty boundary tissues. To overcome this problem, an intuitive fuzzy attribute is embedded into the IFCM-MS. Experiments performed on real brain tumor images demonstrate that our IFCM-MS has low noise sensitivity and high segmentation accuracy.

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