CLUSTERING OF STATE UNIVERSITIES IN INDONESIA BASED ON PRODUCTIVITY OF SCIENTIFIC PUBLICATIONS USING K-MEANS AND K-MEDOIDS

Scientific publication is a measure of the performance of a university. Universities that are owned and operated by the government and whose establishment is carried out by the President of Republic Indonesia are state universities (PTN). One of the efforts that can be made to determine the quantity...

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Main Authors: Ermawati Ermawati, Idhia Sriliana, Riry Sriningsih
Format: Article
Language:English
Published: Universitas Pattimura 2023-09-01
Series:Barekeng
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Online Access:https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/8732
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author Ermawati Ermawati
Idhia Sriliana
Riry Sriningsih
author_facet Ermawati Ermawati
Idhia Sriliana
Riry Sriningsih
author_sort Ermawati Ermawati
collection DOAJ
description Scientific publication is a measure of the performance of a university. Universities that are owned and operated by the government and whose establishment is carried out by the President of Republic Indonesia are state universities (PTN). One of the efforts that can be made to determine the quantity and quality of state university scientific publications is to conduct PTN clustering based on the productivity of scientific publications. This clustering aims to see the position of state universities in Indonesia into 3 categories, namely “high”, “medium”, and “low”. One of the clustering methods that can be used is cluster analysis. The cluster analysis used in this study is k-means and k-medoids with Silhoutte's validity. Based on the results of the analysis, it was found that the Silhouette k-means value (0.8018) was higher than the Silhouette k-medoids value (0.7281). Therefore, in this case, it can be concluded that the k-means method is better than the k-medoids. The results of cluster analysis using K-Means are 1) PTN with high productivity of scientific publications, namely ITB, ITS, UGM, and UI. The four PTNs are PTN as Legal Entity (PTN-BH) located in Java, 2) PTN with medium scientific publication productivity consists of 16 PTN which were dominated by PTN-BH and PTN as Public Service Board (PTN-BLU) with the largest location in Java, and 3) PTN with low scientific publication productivity consisted of 102 PTN which were dominated by PTN as general state financial management (PTN-Satker) with most locations outside Java.
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spelling doaj-art-3064c67ceae2464d8eacb9e9b148f68d2025-08-20T03:35:54ZengUniversitas PattimuraBarekeng1978-72272615-30172023-09-011731617163010.30598/barekengvol17iss3pp1617-16308732CLUSTERING OF STATE UNIVERSITIES IN INDONESIA BASED ON PRODUCTIVITY OF SCIENTIFIC PUBLICATIONS USING K-MEANS AND K-MEDOIDSErmawati Ermawati0Idhia Sriliana1Riry Sriningsih2Department of Mathematics, Faculty of Science and Technology, Universitas Islam Negeri Alauddin Makassar, IndonesiaDepartment of Statistics, Faculty of Mathematics and Natural Science, Universitas Bengkulu, IndonesiaDepartment of Mathematics, Faculty of Mathematics and Natural Science, Universitas Negeri Padang, IndonesiaScientific publication is a measure of the performance of a university. Universities that are owned and operated by the government and whose establishment is carried out by the President of Republic Indonesia are state universities (PTN). One of the efforts that can be made to determine the quantity and quality of state university scientific publications is to conduct PTN clustering based on the productivity of scientific publications. This clustering aims to see the position of state universities in Indonesia into 3 categories, namely “high”, “medium”, and “low”. One of the clustering methods that can be used is cluster analysis. The cluster analysis used in this study is k-means and k-medoids with Silhoutte's validity. Based on the results of the analysis, it was found that the Silhouette k-means value (0.8018) was higher than the Silhouette k-medoids value (0.7281). Therefore, in this case, it can be concluded that the k-means method is better than the k-medoids. The results of cluster analysis using K-Means are 1) PTN with high productivity of scientific publications, namely ITB, ITS, UGM, and UI. The four PTNs are PTN as Legal Entity (PTN-BH) located in Java, 2) PTN with medium scientific publication productivity consists of 16 PTN which were dominated by PTN-BH and PTN as Public Service Board (PTN-BLU) with the largest location in Java, and 3) PTN with low scientific publication productivity consisted of 102 PTN which were dominated by PTN as general state financial management (PTN-Satker) with most locations outside Java.https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/8732clusteringk-meansk-medoidsscientific publications
spellingShingle Ermawati Ermawati
Idhia Sriliana
Riry Sriningsih
CLUSTERING OF STATE UNIVERSITIES IN INDONESIA BASED ON PRODUCTIVITY OF SCIENTIFIC PUBLICATIONS USING K-MEANS AND K-MEDOIDS
Barekeng
clustering
k-means
k-medoids
scientific publications
title CLUSTERING OF STATE UNIVERSITIES IN INDONESIA BASED ON PRODUCTIVITY OF SCIENTIFIC PUBLICATIONS USING K-MEANS AND K-MEDOIDS
title_full CLUSTERING OF STATE UNIVERSITIES IN INDONESIA BASED ON PRODUCTIVITY OF SCIENTIFIC PUBLICATIONS USING K-MEANS AND K-MEDOIDS
title_fullStr CLUSTERING OF STATE UNIVERSITIES IN INDONESIA BASED ON PRODUCTIVITY OF SCIENTIFIC PUBLICATIONS USING K-MEANS AND K-MEDOIDS
title_full_unstemmed CLUSTERING OF STATE UNIVERSITIES IN INDONESIA BASED ON PRODUCTIVITY OF SCIENTIFIC PUBLICATIONS USING K-MEANS AND K-MEDOIDS
title_short CLUSTERING OF STATE UNIVERSITIES IN INDONESIA BASED ON PRODUCTIVITY OF SCIENTIFIC PUBLICATIONS USING K-MEANS AND K-MEDOIDS
title_sort clustering of state universities in indonesia based on productivity of scientific publications using k means and k medoids
topic clustering
k-means
k-medoids
scientific publications
url https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/8732
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AT idhiasriliana clusteringofstateuniversitiesinindonesiabasedonproductivityofscientificpublicationsusingkmeansandkmedoids
AT rirysriningsih clusteringofstateuniversitiesinindonesiabasedonproductivityofscientificpublicationsusingkmeansandkmedoids