| dc.contributor.author | Yuliani Setia Dewi | |
| dc.date.accessioned | 2014-04-01T23:48:45Z | |
| dc.date.available | 2014-04-01T23:48:45Z | |
| dc.date.issued | 2014-04-01 | |
| dc.identifier.issn | 1411-6669 | |
| dc.identifier.uri | http://repository.unej.ac.id/handle/123456789/56609 | |
| dc.description.abstract | Various clustering algorithms have been developed to group data into clusters.
This paper describes clustering objects with mixed categorical and numeric
data types. The methods used are two step clustering and transforms mixed
data using nonlinear principal component analysis then groups the output
resulted using hierarchical aglomerative clustering. The results show that the
number of optimal cluster using both methods have the same optimal number
of cluster but the rank of ratios of distance measure and distribution of cluster
membership are different. | en_US |
| dc.language.iso | other | en_US |
| dc.relation.ispartofseries | Majalah Ilmiah Matematika dan Statistika;Volume 13, Juni 2013 | |
| dc.subject | Two step clustering, nonlinear principal component analysis, mixed data, transform | en_US |
| dc.title | ANALISIS CLUSTER UNTUK DATA CAMPURAN KATEGORIK DAN NUMERIK 80 (Cluster Analysis for Mixed Cagtegorical and Numeric Data Types) | en_US |
| dc.type | Article | en_US |
