PERBANDINGAN RENTANG DATA METRIC PADA ALGORITMA WARD’S TERHADAP DATA CLUSTERING

SENA, AKHMAD and Yunita, Yunita and Miraswan, Kanda Januar (2021) PERBANDINGAN RENTANG DATA METRIC PADA ALGORITMA WARD’S TERHADAP DATA CLUSTERING. Undergraduate thesis, Sriwijaya University.

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Abstract

Clustering is a branch of data mining methodology which objective is to cluster multiple objects to form a group of different clusters, some of the algorithm that have been applied in this methodology is Ward’s. In the application of clustering method, a lot of factor can affect the results of cluster, one of them is distance vector method which might affect the cluster result by a huge margin. In Ward’s algorithms, the use of Euclidean distance often gives better cluster results with relatively lower DBI index score compared to when using another distance vector methods.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Data mining, Distance Vector , Ward’s , Davies Bouldin Index
Subjects:	Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA76.Z55 Apache Hadoop (Computer file) Electronic data processing--Distributed processing. File organization (Computer science) Data mining. Streaming technology (Telecommunications)
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Akhmad Sena
Date Deposited:	05 Nov 2021 01:36
Last Modified:	05 Nov 2021 01:36
URI:	http://repository.unsri.ac.id/id/eprint/56462

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