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PERBANDINGAN ALGORITMA K-MEANS DAN K-MEDOIDS DALAM CLUSTERING RATA-RATA PENAMBAHAN KASUS COVID-19 BERDASARKAN KOTA/KABUPATEN DI PROVINSI SUMATERA SELATAN

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The spread is quite wide and fast, making the Covid-19 pandemic in South Sumatra have a negative impact on all sectors such as health, employment and the economy. With the government's policy of grouping the Covid-19 handling areas into 4 zones, it is necessary to evaluate whether the grouping of these areas is appropriate using data mining clustering techniques with the K-Means and K-Medoids algorithms. From the results of testing the K-Means algorithm, the best DBI value is 0.078 at K=2. While the K-Medoids algorithm gives the best DBI value is 0.250 at K=3. So that the conclusions obtained, it is recommended that the distribution of the Covid-19 handling area in the province of South Sumatra be divided into 2 clusters (namely Palembang City and Outside Palembang City) or into 3 clusters (namely Palembang City, close to Palembang City and far from Palembang City).

Availability
Inventory Code Barcode Call Number Location Status
2207002388T74978T749782022Central Library (Referens)Available but not for loan - Not for Loan
Detail Information
Series Title
-
Call Number
T749782022
Publisher
Inderalaya : Prodi Sistem Informasi, Fakultas Ilmu Komputer.,
Collation
xiv, 66 hlm.; ilus.; 29 cm
Language
Indonesia
ISBN/ISSN
-
Classification
004.07
Content Type
-
Media Type
-
Carrier Type
-
Edition
-
Subject(s)
Pengolahan Data
Prodi Sistem Informasi
Specific Detail Info
-
Statement of Responsibility
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