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CLUSTERING BODYFAT MENGGUNAKAN ALGORITMA K-MEANS CLUSTERING

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Penilaian

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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.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2307000695	T89973	T899732023	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T899732023

Publisher

Inderalaya : Prodi Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2023

Collation

xiv, 74 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

006.307

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Sistem Pakar
Prodi Teknik Informatika

Specific Detail Info

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Statement of Responsibility

SEPTA

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