Judul: Penggerombolan Propinsi di Indonesia Berdasarkan Indikator Pendidikan Sekolah Lanjutan Atas Menggunakan Metode Ward dan Metode Fuzzy C-means
Abstrak: 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.
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Judul: Cluster Ensemble Analysis for Grouping Districts/Cities in Indonesia Based on Education Quality
Abstrak: Clustering merupakan metode yang cukup populer dan telah banyak digunakan di berbagai bidang. Pengelompokan dalam statistik dilakukan dengan menggunakan analisis gerombol. Penelitian ini bertujuan untuk mengelompokkan kabupaten/kota berdasarkan kualitas pendidikan dengan dua tipe data yang berbeda. Cluster ensemble adalah metode yang tepat untuk mengelompokkan data campuran. Metode ini menggabungkan hasil dari dua metode penggerombolan yang berbeda yang kemudian digabungkan untuk memperoleh hasil akhir. Metode untuk data numerik menggunakan metode agglomerative hierarchical clustering dan untuk data kategorik menggunakan algoritma squeezer. Pengelompokan 514 kabupaten/kota di Indonesia berdasarkan 18 peubah menghasilkan 3 gerombol. Jumlah anggota setiap gerombol adalah 446, 51, dan 17. Gerombol 1 merupakan wilayah dengan kualitas pendidikan terbaik berdasarkan indikator yang digunakan. Gerombol 2 dicirikan dengan rataan RLS dan HLS tertinggi serta rataan rasio murid terhadap guru yang paling besar dan sangat jauh dari batas ideal. Sementara itu, gerombol 3 menjadi gerombol dengan kualitas pendidikan yang paling rendah. Gerombol ini dicirikan dengan rataan RLS dan persentase guru terkualifikasi SMK yang sangat kecil., Clustering is a method that is quite popular and has been widely used in various fields. Clustering in statistics is done by using cluster analysis. This research aims to classify regions based on the quality of education with two different data types. Cluster ensemble are an appropriate method for clustering mixed data. This method combines the results of two different clustering methods which are then obtained into the final result. The method for numeric data uses the hierarchical clustering method and for categorical data uses the squeezer algorithm. Clustering of 514 district/cities in Indonesia based on 18 variables resulted in 3 clusters. The number of members of each cluster is 446, 51, and 17. Cluster 1 is the region with the best quality of education based on the indicators used. Cluster 2 is characterized by the highest average RLS and HLS and the highest student to teacher ratio which is very far from the ideal limit. Meanwhile, cluster 3 is the group with the lowest quality of education. This cluster is characterized by a very small average RLS and percentage of SMK qualified teachers.
Keyword: cluster ensemble, data campuran, pendidikan, squeezer

Judul: Hydroxyapatite-Chitosan Composite Coating on Stainless Steel 316 to Improve Corrosion Resistance
Abstrak: Metals that were used in bone implantation should have good corrosion resistance that were not easily corroded when implanted into the body. Metal corrosion resistance of stainless steel 316 can be enhanced through the metal coating by hydroxyapatite-chitosan composite with composition ratio of hydroxyapatite (gram) and chitosan 3% (mL) 0.2:0, 0.2:0.1, 0.2:0.5, 0.2:1.0, and 0.2:1.5. Besides improving the corrosion resistance of metal, the presence of chitosan also maintain the position of hydroxyapatite on metal surfaces. Corrosion resistance increases with increasing amount of chitosan added and the best composition of hydroxyapatite-chitosan composite was 0.2:1.0.
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