Penggerombolan Mutu SMA/MA per Provinsi Berdasarkan Hasil Akreditasi Menggunakan Metode Fuzzy C-Means
Keywords:cluster analysis, degree of membership, fuzzy c-means, validity index
Mapping the quality of education in Indonesia needs to be studied so that the provincial government, as the institution responsible for secondary education management policies, can more easily determine priorities and what actions will be taken to improve the quality of education in Indonesia. One of the analytical methods that can be used to map the quality of education is fuzzy c-means. This research aims to classify the quality maps of provinces in Indonesia based on the results of SHS/MA accreditation using the fuzzy c-means method. The fuzzy c-means method can show the probability of objects entering a cluster with a degree of membership. The optimum cluster sizes obtained were 2 and 3. The final solution with cluster size 2 was 12 provinces categorized in cluster 1 and 22 provinces categorized in cluster 2. Clustering with cluster size 3 resulted in cluster 1 consisting of 11 provinces, cluster 2 consisting of 16 provinces, and cluster 3, which consists of 7 provinces. The main character of cluster 1 is a high national education standard score, while the main character of cluster 2 is a low national education standard score. Then the main character of group 3 is the national standard score, whose value is around the national average.