Text

CLUSTERING TARAF KESEJAHTERAAN KABUPATEN/KOTA DI INDONESIA MENGGUNAKAN KOMBINASI METODE K-MEANS DAN HIERARCHICAL CLUSTERING

---

Penilaian

---

The problem of people's welfare is a problem that must be faced by developing countries like Indonesia. Many indicators influence the level of people's welfare. Therefore, it is necessary to group districts / cities to assist in policy making. This study uses a combination of K-means and Hierarchical clustering methods. K-means has the ability to classify large amounts of data with relatively fast and efficient computation time. However, the results of K-means clustering are highly dependent on the initial center of the cluster. Therefore, the K-means method is combined with Hierarchical clustering to determine the initial center of the cluster. The results of grouping will be evaluated using the Davies Bouldin Index (DBI) and the Silhouette Index (SI). The DBI value of the combination of K-means and Hierarchical clustering has the lowest value of 0.51 with 9 clusters compared to only using the K-means method of 0.58 with 7 clusters. The SI value of the combination of K-means and Hierarchical clustering has the highest value of 0.92 with 9 clusters compared to only using the K-means method of 0.89 with 7 clusters.

---

Availability

Inventory Code	Barcode	Call Number	Location	Status
2007000856	T39137	T391372020	Central Library (REFERENCES)	Available but not for loan - Not for Loan

Detail Information

Series Title

-

Call Number

T391372020

Publisher

Indralaya : Prodi Teknik Informatika, Fakultas Ilmu Komputer., 2020

Collation

xv, 85 hlm.; ilus., tab.: 28 cm

Language

Indonesia

ISBN/ISSN

-

Classification

005.07

Content Type

Text

Media Type

-

Carrier Type

-

Edition

-

Subject(s)

Prodi Teknik Informatika, Fakultas Ilmu Komputer
Taraf Kesejahteraan

Specific Detail Info

-

Statement of Responsibility

TUTI

Other version/related

File Attachment

Comments

---

You must be logged in to post a comment