Penggerombolan Hasil Ujian Nasional Menggunakan K-Rataan Samar

Authors

  • Nouval Habibie Department of Statistics, IPB University, Indonesia
  • Akbar Rizki Department of Statistics, IPB University, Indonesia
  • Pika Silvianti Department of Statistics, IPB University, Indonesia

DOI:

https://doi.org/10.29244/xplore.v10i1.365

Keywords:

cluster analysis, fuzzy c-means, mapping, national examination score

Abstract

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 don’t have any districts/cities belong to cluster A.

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Published

2021-01-01

How to Cite

Habibie, N., Rizki, A., & Silvianti, P. (2021). Penggerombolan Hasil Ujian Nasional Menggunakan K-Rataan Samar. Xplore: Journal of Statistics, 10(1), 41–54. https://doi.org/10.29244/xplore.v10i1.365

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