TY  - JOUR
T1  - University Webometrics Ranking using Multicriteria
Decision Analysis: Entropy and TOPSIS Method
AU - Jati, Handaru 
JO  - The Social Sciences
VL  - 13
IS  - 3
SP  - 763
EP  - 765
PY  - 2018
DA  - 2001/08/19
SN  - 1818-5800
DO  - sscience.2018.763.765
UR  - https://makhillpublications.co/view-article.php?doi=sscience.2018.763.765
KW  - webometrics
KW  -multicriteria
KW  -Ranking
KW  -MCDA
KW  -entropy
KW  -TOPSIS
AB  - For many academic institutions, among which are the universities the web has become an interesting
tool. This web presence of academic institutions has led the researcher, academic and scientific publication in
this environment to use this web to reflect their activities. This study explores the webometrics ranking for
world universities. The webometrics for world universities were calculated by using two quantitative techniques
in Multicriteria Decision Analysis (MCDA) which are Entropy method and the Technique for Order of
Preference by Similarity to Ideal Solution (TOPSIS). This calculation was made based on four key indices: size,
the visibility of the website, rich content size which is the volume of published information and scholar. The
basic principle of the TOPSIS method is that the chosen alternative should have the "shortest distance" from
the ideal solution and the "farthest distance" from the "negative-ideal" solution. For the case studies
investigated the entropy and TOPSIS technique is effective and simple in terms of computational
implementation. Its advantages is that the algorithm does not require tuning any parameters. These models
efficiently help evaluators to determine with a strategic view for future developments and more aspect by using
multicriteria decision analysis. It concludes by acknowledging that webometrics ranking systems are viewed
differently by different stakeholders and hence can be approached in different ways.
ER  -