KLASIFIKASI DATA DENGAN METODE K-MEANS DALAM ANALISIS KELOMPOK - MOCH. IDRIS, 089511369 (2000)
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.