STUDI KOMPARATIF PENERAPAN METODE HIERARCHICAL, K-MEANS DAN SELF ORGANIZING MAPS (SOM) CLUSTERING PADA BASIS DATA


Undang Syaripudin(1*), Ijang Badruzaman(2), Erwan Yani(3), Dede K(4), M. Ramdhani(5)

(1) Teknik Informatika UIN Sunan Gunung Djati Bandung, Indonesia
(2) Teknik Informatika UIN Sunan Gunung Djati Bandung, Indonesia
(3) AMIK Garut, Indonesia
(4) AMIK Garut, Indonesia
(5) AMIK Garut,  
(*) Corresponding Author

Abstract


This study identifies the results of some test results clustering methods. The data set used in this test method Clustering. The third method of clustering based on these factors than the size of the data set and the extent of the cluster. The test results showed that the SOM algorithm produces better accuracy in classifying objects into matching groups. K-means algorithm is very good when using large data sets and compared with Hierarchical SOM algorithm. Hierarchical grouping and SOM showed good results when using small data sets compared to using k-means algorithm.

Full Text:

PDF

References


Santosa, Budi. 2007. Data Mining. Teknik Pemanfaatan Data untuk Keperluan Bisnis, First Edition ed. Yogyakarta: Graha Ilmu.

Prasetyo, Eko. 2012. Data Mining Konsep dan Aplikasi Menggunakan Matlab. Yogyakarta : penerbit andi.

Eisen, M. 1998. Cluster and Tree View Manual. Stanford University. Japan.

Abu Abbas, Osama. 2007. Comparisons Between Data Clustering Algorithms. Computer Science Department, Yarmouk University, Jordan

K. Arai and A. R. Barakbah. 2007. "Hierarchical K-means: an algorithm for centroids initialization for Kmeans,". Saga University.

Alfina, Tahta. 2012. Analisa Perbandingan Metode Hierarchical Clustering, K-means dan Gabungan Keduanya dalam Cluster Data. Institut Teknologi Sepuluh Nopember.

Latiffaturrahman. 2010. perbandingan hasil penggerombolan metode k-means, fuzzy k-means dan two step cluster. Institut Pertanaian Bogor.

Wahanani, Nursinta Adi. 2012. Optimasi Clustering K-Means Dengan Algoritma Genetika Multiobyektif. Institut Pertanaian Bogor.

Shandy, Liesca Levy. 2008. Perbandingan Metode Diskretisasi Data Partisi Intuitif dan K-Means Clustering Terhadap Pembuatan Pohon Keputusan. Institut Pertanaian Bogor.

Edward. 2006. Clustering Menggunakan Self Organizing Maps. Institut Pertanaian Bogor.

Fatansyah. 1999. Basis Data. Bandung: Informatika.