Pengelompokkan Kabupaten/Kota Di Sulawesi Berdasarkan Indikator Pendidikan Menggunakan Analisis Klaster Average Linkage Dan Median Linkage

Abstract

Cluster analysis is included in the method of multivariate analysis of interdependence. Cluster analysis is a multivariate technique that classifies objects into different groups between one group and another group. This research is applied to the case of education indicators, education is important for improving the quality of human resources. Educational indicators are a measuring tool used to see how well the quality of education. Educational indicators are classified using average linkage and median linkage. The results of the analysis showed that the median linkage obtained a standard deviation ratio value of 0.061 smaller than the standard deviation ratio average linkage value of 0.078. The method that has the smallest ratio is the method with the best performance. So that grouping City Districts in Sulawesi based on education indicators in 2017 is better to use the median linkage and obtained 5 clusters formed.

K-means clustering for classifying the quality management of secondary education in Indonesia

“…In a comprehensive direction, the clustering process enables us to map the quality of education (Ananda, 2019;Nugraha & Hairani, 2018;Oktavianty & Handayani, 2019;Subanar, 2011). In response to this, every province's management of senior secondary schools is pivotal for in-depth analysis.…”

“…Cluster analysis was outlined by performing the Kmeans approach in distributing senior secondary school teachers in Indonesia (Widiyaningtyas et al, 2017). Other studies also exposed the application of cluster analysis in mapping the quality of education in Indonesian school settings (Ananda, 2019;Nugraha & Hairani, 2018;Oktavianty et al, 2019;Prayoga & Zain, 2016;Wijayanto, 2016).…”