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

Main Authors: Syaripudin, Undang; Teknik Informatika UIN Sunan Gunung Djati Bandung, Badruzaman, Ijang; Teknik Informatika UIN Sunan Gunung Djati Bandung, Yani, Erwan; AMIK Garut, K, Dede; AMIK Garut, Ramdhani, M.; AMIK Garut
Format: Article info application/pdf eJournal
Bahasa: eng
Terbitan: JURNAL ISTEK , 2015
Online Access: http://journal.uinsgd.ac.id/index.php/istek/article/view/239
http://journal.uinsgd.ac.id/index.php/istek/article/view/239/253
Daftar Isi:
  • 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.