| dc.contributor.advisor | Sembiring, Pasukat | |
| dc.contributor.author | Hsb, Siti Sahara | |
| dc.date.accessioned | 2025-02-19T04:15:19Z | |
| dc.date.available | 2025-02-19T04:15:19Z | |
| dc.date.issued | 2022 | |
| dc.identifier.uri | https://repositori.usu.ac.id/handle/123456789/101443 | |
| dc.description.abstract | Cluster is a multivariate technique that aims to classify objects into different
groups from one group to another. Objects that have been classified in one cluster
are objects that have the same relative distance proximity to other objects. In this
study, the distance used is Euclidean. The purpose of this study was to classify
regencies/cities in North Sumatra based on data on Covid-19 cases in North
Sumatra on November 4, 2021 and to find out the characteristics of the cluster
formed based on the category of high (Cluster 1), medium (Cluster 2), and low
(Cluster 3). The results of this study alone succeeded in classifying Covid-19
cases in 33 regencies/cities in North Sumatra where there were 3 clusters, namely
Cluster 1 had 1 member, Cluster 2 had 13 members, Cluster 3 had 18 members,
and 1 Regency/Municipal. Cities are Outliers. | en_US |
| dc.language.iso | id | en_US |
| dc.publisher | Universitas Sumatera Utara | en_US |
| dc.subject | Cluster | en_US |
| dc.subject | K-Means | en_US |
| dc.subject | Grouping | en_US |
| dc.title | Pengelompokan Data Kasus Covid-19 di Sumatera Utara dengan Metode K-Means | en_US |
| dc.title.alternative | Grouping of Data on Covid-19 Cases in North Sumatra Using the K-Means Method | en_US |
| dc.type | Thesis | en_US |
| dc.identifier.nim | NIM180823027 | |
| dc.identifier.nidn | NIDN8801690019 | |
| dc.identifier.kodeprodi | KODEPRODI44201#Matematika | |
| dc.description.pages | 74 Pages | en_US |
| dc.description.type | Skripsi Sarjana | en_US |
| dc.subject.sdgs | SDGs 4. Quality Education | en_US |
