CLUSTERING BODYFAT MENGGUNAKAN ALGORITMA K-MEANS CLUSTERING

NALA, INDA and Yusliani, Novi and Miraswan, Kanda Januar (2023) CLUSTERING BODYFAT MENGGUNAKAN ALGORITMA K-MEANS CLUSTERING. Undergraduate thesis, Sriwijaya University.

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Abstract

Clustering is one of several techniques used in data mining, which is to group data based on the degree of similarity. The greater the degree of similarity of the data, it will be placed in the same cluster. One of the clustering techniques is K-Means Clustering. This study aims to determine the best cluster results from bodyfat data used as a reference in providing appropriate services based on the average centroid value in each cluster affected by 15 attributes. The clustering results are then evaluated using the Davies Bouldin Index (DBI) value. In this study, after testing 3 times, the lowest DBI evaluation results were obtained in Cluster 9 from Cluster 2 to 10 of the number of clusters. The final results obtained by Centroid 1 to 9 sequentially have the number of members which are 24,17, 22, 55, 31, 30, 25, 16, and 32.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Algoritma K-Means, Clustering
Subjects:	T Technology > T Technology (General) > T58.4 Managerial control systems Information technology. Information systems (General)
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Inda Nala
Date Deposited:	27 Feb 2023 03:03
Last Modified:	27 Feb 2023 03:03
URI:	http://repository.unsri.ac.id/id/eprint/89973

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