Clustering Province in Indonesia Building on Indicator of Senior High School Education Use Ward Method and Fuzzy C-Means
Penggerombolan Propinsi di Indonesia Berdasarkan Indikator Pendidikan Sekolah Lanjutan Atas Menggunakan Metode Ward dan Metode Fuzzy C-means
Date
2010Author
Mulyanto, Anton
Djuraidah, Anik
Sulvianti, Itasia Dina
Metadata
Show full item recordAbstract
Education is one of factor success build a nation, not expection of Indonesia. Indonesia had done various education programs to create even distribution of education at all region in Indonesia. One of methods can use to knows this condition is cluster analysis. The purposes of this research are to clustering province in Indonesia building on indicator of senior high school education and to compare the result between Ward method and Fuzzy C-means. Data used in this research was secondary data indicator of senior high school education 2008, which obtained from Badan Pusat Statistik (BPS), Jakarta. Object used consist of 33 province in Indonesia. Indicator of senior high school education are: (1) Broken School Rate; (2) Ratio of Student and Class; (3) Ratio of Student and Teacher; (4) Ratio of Class and School; and (5) Participation Crude Rate. First step is used descriptive analysis to know the condition of senior high school education at each province. Cluster analysis use Ward method and Fuzzy C-means method. The reason they chosen are resulting a small variance at cluster and data used in this research is a few. Sum of optimum clustering at Fuzzy C-means is obtained from Index Xie Beni criteria. Before conducting cluster analysis, assumptions of correlation between variable must be checked. To evaluated it used Principal Componen Analysis. Transformation result of Principal Componen Analysis shows percentage variance cumulative reach 93% at fourth main component. The determining which the best method used different test mean vector use Lambda Wilks’ criteria and minimum objective function. As a result, characteristic between Ward method and Fuzzy Cmeans method is not different. Sum of cluster obtained at Ward method and Fuzzy C-means are 3 cluster. According to Lambda Wilks’ criteria and minimum objective function, Fuzzy C-means method better than Ward method for data of indicator of senior high school education.