Penggerombolan Hasil Ujian Nasional Menggunakan K-Rataan Samar
Keywords:cluster analysis, fuzzy c-means, mapping, national examination score
National examination scores can be a basis for the government to make a mapping of education quality in order to increase it. The mapping can be done by using fuzzy cluster analysis. The objective of this experiment is to cluster districts/cities in Indonesia based on national examination score in natural and social science in 2014/2015 until 2017/2018 school year by using the fuzzy c-means method. The evaluation criteria that will be used are the standard deviation ratio, silhouette coefficient, and Xie Beni index. The best cluster size is two clusters, A and B. The clustering result shows cluster A has a higher mean from each subject than cluster B. Therefore, cluster A will be categorized as good, whereas cluster B as bad. The proportion of districts/cities that belong to cluster A decreased each year. The final cluster result can be determined by the mean of its degree of membership from those four school years. The analysis results show that the distribution of education quality is dominated in Java Island and squatter cities. East Nusa Tenggara, West Sulawesi, Central Sulawesi, and North Kalimantan donâ€™t have any districts/cities belong to cluster A.