TY  - JOUR
T1  - Higher Education Clustering in Indonesia by using k-means and
Geographical Similarity Methods
AU - Daru Kusuma, Purba AU - Rachmaningrum, Nilla 
JO  - Journal of Engineering and Applied Sciences
VL  - 14
IS  - 19
SP  - 7193
EP  - 7209
PY  - 2019
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2019.7193.7209
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2019.7193.7209
KW  - Clustering
KW  -k-means
KW  -education Indonesia
KW  -geographic similarity
KW  -computational methods
KW  -institution
AB  - Diverse quality and equality in higher education has been concerned by government of Indonesia.
It is because these aspects have positive correlation with the country development and competitiveness.
Meanwhile, improvement policy should be supported by better perspective and mapping about the condition
of the higher education in this country. Although, ministry of research and higher education of Indonesia has
published statistical data, the analysis of it is very limited. Based on this problem, we use clustering method
to analyze this higher education statistic data, so that, new perspective and understanding can be explored. In
this research, we use two computational methods: k-means and geographical similarity, so that, the analysis
can be enriched. In this research, we also compare the condition in private institution and public institution.
Result shows that in some aspects, there is disparity between private institution and public institution.
Meanwhile in some aspect, there is disparity between Java Region and other regions in Indonesia.
ER  -