Article Per Year (5 Year)
p-Index From 2019 - 2024
0.408
P-Index
This Author published in this journals
All Journal TEKNOLOGI: Jurnal Ilmiah Sistem Informasi
Retnosari, Hesti
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Mathematics

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Penerapan metode k-means clustering data COVID-19 di Provinsi Jakarta Untoro, Meida Cahyo; Anggraini, Leslie; Andini, Maria; Retnosari, Hesti; Nasrulloh, M. Anas
TEKNOLOGI: Jurnal Ilmiah Sistem Informasi Vol 11, No 2 (2021): July
Publisher : Universitas Pesantren Tinggi Darul 'Ulum (Unipdu) Jombang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/teknologi.v11i2.2323

Abstract

The disease epidemic that attacked the respiratory area and was detected in Indonesia starting in early 2020 is the Corona Virus (COVID-19). This virus's spread is relatively easy, namely through droplets from infected patients, so that the spread is very rapid. This research was conducted to cluster the data on Covid-19 cases in Jakarta Province considering that Jakarta is the starting point for the first case of Corona in Indonesia and until now has become one of the most significant contributors to COVID-19 issues in Indonesia, namely as of December 2020 positive cases of Covid-19 reached 154,000. Souls with the healing of 139.0000 souls. The grouping was carried out based on positive and dead patients from each urban village in Jakarta Province. This study uses the k-means Method to cluster in the handling of COVID-19 cases with 2 clusters. Data distribution in cluster 1 consists of 173 data and 18 data in cluster 2. The use of k-means in this study provides information on areas with the highest and lowest number of positive cases and the highest and lowest cure rates that can be used as an evaluation in handling the Covid-virus 19.
Penerapan metode k-means clustering data COVID-19 di Provinsi Jakarta Untoro, Meida Cahyo; Anggraini, Leslie; Andini, Maria; Retnosari, Hesti; Nasrulloh, M. Anas
TEKNOLOGI: Jurnal Ilmiah Sistem Informasi Vol 11, No 2 (2021): July
Publisher : Universitas Pesantren Tinggi Darul 'Ulum (Unipdu) Jombang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/teknologi.v11i2.2323

Abstract

The disease epidemic that attacked the respiratory area and was detected in Indonesia starting in early 2020 is the Corona Virus (COVID-19). This virus's spread is relatively easy, namely through droplets from infected patients, so that the spread is very rapid. This research was conducted to cluster the data on Covid-19 cases in Jakarta Province considering that Jakarta is the starting point for the first case of Corona in Indonesia and until now has become one of the most significant contributors to COVID-19 issues in Indonesia, namely as of December 2020 positive cases of Covid-19 reached 154,000. Souls with the healing of 139.0000 souls. The grouping was carried out based on positive and dead patients from each urban village in Jakarta Province. This study uses the k-means Method to cluster in the handling of COVID-19 cases with 2 clusters. Data distribution in cluster 1 consists of 173 data and 18 data in cluster 2. The use of k-means in this study provides information on areas with the highest and lowest number of positive cases and the highest and lowest cure rates that can be used as an evaluation in handling the Covid-virus 19.
Co-Authors Andini, Maria Anggraini, Leslie Nasrulloh, M. Anas Untoro, Meida Cahyo