KLASIFIKASI DATA DENGAN METODE K-MEANS DALAM ANALISIS KELOMPOK
The aim of this thesis is to give an alternative solution for classification of the observed objects in cluster analysis. The number of group of data observation is frequently unknown, so the hierarchical method is needed. The non-hierarchical methods that use K-Means algorithm relocate observations...
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id-langga.485882017-06-08T16:18:06Z http://repository.unair.ac.id/48588/ KLASIFIKASI DATA DENGAN METODE K-MEANS DALAM ANALISIS KELOMPOK MOCH. IDRIS, 089511369 BL350-385 Classification of Religions K300-304 Classification of law. Typology The aim of this thesis is to give an alternative solution for classification of the observed objects in cluster analysis. The number of group of data observation is frequently unknown, so the hierarchical method is needed. The non-hierarchical methods that use K-Means algorithm relocate observations in appropriate group. The result of discussion is the K-means method can be used in classification process of observations in cluster analysis. The distinction of initial value of the central of the group gives the different result in classification process. The spread of observations that will be grouped influence the result in classification process. 2000 Thesis NonPeerReviewed text id http://repository.unair.ac.id/48588/7/KK%20MPM%2033-00%20IDR%20K.pdf MOCH. IDRIS, 089511369 (2000) KLASIFIKASI DATA DENGAN METODE K-MEANS DALAM ANALISIS KELOMPOK. Skripsi thesis, Universitas Airlangga. http://lib.unair.ac.id |
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BL350-385 Classification of Religions K300-304 Classification of law. Typology |
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BL350-385 Classification of Religions K300-304 Classification of law. Typology MOCH. IDRIS, 089511369 KLASIFIKASI DATA DENGAN METODE K-MEANS DALAM ANALISIS KELOMPOK |
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The aim of this thesis is to give an alternative solution for classification of the observed objects in cluster analysis. The number of group of data observation is frequently unknown, so the hierarchical method is needed. The non-hierarchical methods that use K-Means algorithm relocate observations in appropriate group.
The result of discussion is the K-means method can be used in classification process of observations in cluster analysis. The distinction of initial value of the central of the group gives the different result in classification process. The spread of observations that will be grouped influence the result in classification process. |
format |
Theses and Dissertations NonPeerReviewed |
author |
MOCH. IDRIS, 089511369 |
author_facet |
MOCH. IDRIS, 089511369 |
author_sort |
MOCH. IDRIS, 089511369 |
title |
KLASIFIKASI DATA DENGAN METODE K-MEANS DALAM ANALISIS KELOMPOK |
title_short |
KLASIFIKASI DATA DENGAN METODE K-MEANS DALAM ANALISIS KELOMPOK |
title_full |
KLASIFIKASI DATA DENGAN METODE K-MEANS DALAM ANALISIS KELOMPOK |
title_fullStr |
KLASIFIKASI DATA DENGAN METODE K-MEANS DALAM ANALISIS KELOMPOK |
title_full_unstemmed |
KLASIFIKASI DATA DENGAN METODE K-MEANS DALAM ANALISIS KELOMPOK |
title_sort |
klasifikasi data dengan metode k-means dalam analisis kelompok |
publishDate |
2000 |
url |
http://repository.unair.ac.id/48588/7/KK%20MPM%2033-00%20IDR%20K.pdf http://repository.unair.ac.id/48588/ http://lib.unair.ac.id |
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1681146026180739072 |