CLUSTERING STATUS GIZI BALITA DI PUSKESMAS TALANG BULUH MENGGUNAKAN KOMBINASI METODE K-MEANS DAN HIERARCHICAL CLUSTERING

MUHAMMAD, NAUFAL AL HAFIF and Alvi, Syahrini Utami and Kanda, Januar Miraswan (2021) CLUSTERING STATUS GIZI BALITA DI PUSKESMAS TALANG BULUH MENGGUNAKAN KOMBINASI METODE K-MEANS DAN HIERARCHICAL CLUSTERING. Undergraduate thesis, Sriwijaya University.

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Abstract

Malnutrition is one of the health problems that often afflicts toddlers in Indonesia, one of which is caused by the consumption of food given to toddlers. Therefore, it is necessary to strive for grouping the nutritional status of toddlers with the aim of getting the status of excessive, good, and bad nutrition by using a combination method of the K-means algorithm and Hierarchical Clustering. The K-means method has the ability to group large amounts of data in a fast time. However, the disadvantage is that it depends on the initial center of the cluster. Therefore, a hierarchical method was used to determine the initial center of the cluster. The results of the grouping are then evaluated using the Davies Bouldin Index (DBI) and the Silhouette Index (SI) so that after the test the results of the lowest DBI evaluation value are 0.622 with the K-Cluster value being in the 2nd K-Cluster and the highest SI at 0.906 with a K value. -The cluster is in the 2nd K-Cluster from K-Cluster 2 to 10 clustering.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Gizi Balita Indonesia, Clustering, K-means, Hierarchical, Davies Bouldin Index, Silhouette Index.
Subjects: T Technology > T Technology (General) > T1-995 Technology (General)
Divisions: 09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User: Muhammad Naufal Al Hafif
Date Deposited: 20 Jan 2022 07:53
Last Modified: 20 Jan 2022 07:53
URI: http://repository.unsri.ac.id/id/eprint/62051

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