dc.contributor.author |
Agustin, Violyn |
|
dc.date.accessioned |
2022-01-19T07:01:46Z |
|
dc.date.available |
2022-01-19T07:01:46Z |
|
dc.date.issued |
2021-07 |
|
dc.identifier.other |
wahyu sari yeni |
|
dc.identifier.uri |
https://repository.unri.ac.id/handle/123456789/10436 |
|
dc.description.abstract |
The spread of disease in Indonesia is a serious problem and must be addressed.
Provinces in Indonesia have different characteristics of the spread of disease in each
region. Characteristics of an area are grouped based on indicators of disease spread,
so that the government can accurately and quickly take disease prevention policies in
an area by grouping. This study discusses the grouping of provinces in Indonesia based
on disease cases in 2019 using a comparison of the K-Means and K-Medoids clustering
methods which include non-hierarchical data grouping methods. The results of this
study indicate that using K-Means obtained 3 provinces in cluster 1, 29 provinces in
cluster 2 and 2 provinces in cluster 3, while using K-Medoids obtained 29 provinces in
cluster 1, 4 provinces in cluster 2 and 1 province. in cluster 3. From the results of
grouping the two methods, a comparison of the best method using cluster validation is
obtained, namely the K-Means method because it has the smallest variance value, which
is 1.010. |
en_US |
dc.description.provenance |
Submitted by wahyu sari yeni (ayoe32@ymail.com) on 2022-01-19T07:01:46Z
No. of bitstreams: 1
Violyn Agustin T_compressed.pdf: 189824 bytes, checksum: e9ce7b366482dfdca5e78064ae157cd5 (MD5) |
en |
dc.description.provenance |
Made available in DSpace on 2022-01-19T07:01:46Z (GMT). No. of bitstreams: 1
Violyn Agustin T_compressed.pdf: 189824 bytes, checksum: e9ce7b366482dfdca5e78064ae157cd5 (MD5)
Previous issue date: 2021-07 |
en |
dc.description.sponsorship |
Jurusan Matematika
Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Riau |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
perpustakaan UR |
en_US |
dc.subject |
Disease |
en_US |
dc.subject |
K-Means |
en_US |
dc.subject |
K-Medoids |
en_US |
dc.subject |
cluster validation |
en_US |
dc.title |
PERBANDINGAN ANALISIS CLUSTERING K-MEANS DAN K-MEDOIDS PADA DATA PENYAKIT DI INDONESIA TAHUN 2019 |
en_US |
dc.type |
Article |
en_US |
dc.contributor.supervisor |
Sirait, Haposan |
|