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All Journal Jurnal Riset Informatika Journal of Informatics and Advanced Computing
Michael Sitorus
BRI Institute
Computer Science & IT

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IMPLEMENTATION OF K-MEANS ALGORITHM FOR CLUSTERING OF COVID-19 VACCINATION IN EAST JAVA WITH ORANGE Michael Sitorus; Cornelia Antonieta Da Costa; Cyntia Larasati
Jurnal Riset Informatika Vol 4 No 3 (2022): Period of June 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1038.206 KB) | DOI: 10.34288/jri.v4i3.401

Abstract

Entering the era of the Covid-19 pandemic, the government has intensively implemented a vaccination program to date. The Covid-19 vaccination program aims to boost the immune system, reduce the risk of transmission, and reduce the severe impact of the virus to achieve group immunity. In its implementation, the Covid-19 vaccination is regulated by the regional government in each province with a policy that requires the Covid-19 vaccination to be vaccinated twice for everyone who meets certain criteria. This study aims to cluster the implementation of vaccination in all areas of East Java province in 2021. The method used in conducting this clustering is the K-Means algorithm. From the results of the study, the results of the division or clustering of regions into three clusters were C1 for the area with the lowest vaccination, namely Pasuruan Regency, C2 for the area with moderate vaccination, namely Kediri City, and C3 for the highest vaccination area, namely Surabaya City. The clustering results obtained based on the K-Means algorithm can be used as input for the East Java Provincial government in evaluating the implementation of the Covid-19 vaccination.
IMPLEMENTATION OF K-MEANS ALGORITHM FOR CLUSTERING OF COVID-19 VACCINATION IN EAST JAVA WITH ORANGE Michael Sitorus; Cornelia Antonieta DC; Cyntia Larasati
Jurnal Riset Informatika Vol. 4 No. 3 (2022): June 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (877.827 KB) | DOI: 10.34288/jri.v4i3.188

Abstract

Entering the era of the Covid-19 pandemic, the government has intensively implemented a vaccination program until now. Covid-19 vaccination programs are implemented to strengthen the immune system, reduce the risk of infection, reduce the severe effects of the virus, and achieve herd immunity. In the implementation, the Covid-19 vaccination is regulated by the regional government in each province with a policy that requires vaccinating Covid-19 twice for everyone with specific criteria supported by movements to wear masks, use hand sanitizers, and diligently wash hands and contact tracing of positive cases. This study aims to demographically cluster the implementation of vaccinations in all areas of East Java province in 2021. The method used in conducting this clustering is the K-Means algorithm using tools, namely Orange. From the results of the study, the results of the division or clustering of regions into three clusters were C1 for the area with the lowest vaccination, namely Pasuruan Regency, C2 for the area with moderate vaccination, namely Kediri City, and C3 for the highest vaccination area, namely Surabaya City.
Data Mining Implementasi Algoritma K-Means Menggunakan Aplikasi Orange dalam Clustering Pencemaran Udara di DKI Jakarta Tahun 2021 Michael Sitorus; Depriansa Fitron; Carolus Agung Segara Wisesa
Journal of Informatics and Advanced Computing (JIAC) Vol 3 No 2 (2022): Journal of Informatics and Advanced Computing (JIAC)
Publisher : Teknik Informatika Universitas Pancasila

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Udara yang bersih merupakan kebutuhan yang tidak hanya perlu dipenuhi manusia, tetapi juga hewan dan tumbuhan. Kualitas udara menjadi penting untuk kehidupan kita agar bisa terhindar dari berbagai penyakit kesehatan. Maka dari itu, diterapkanlah ilmu dari data mining dengan metode k-means clustering dengan perangkat lunak Orange untuk bisa mengelompokkan kategori dari kualitas udara yang berada di DKI Jakarta yang meliputi kualitas udara baik, sedang, dan tidak sehat. Dengan menggunakan data yang diperoleh dari Indeks Standar Pencemaran Udara (ISPU) dari Dinas Lingkungan Hidup Provinsi DKI Jakarta tahun 2021, didapat hasil bahwa cluster 0 atau kategori kualitas udara sedang sebanyak 153 item dan cluster 1 atau udara tidak sehat sebanyak 212 item. Tingkat akurasi dari implementasi Cluster K-Means untuk menentukan kualitas udara di DKI Jakarta adalah 0,9622 atau 96,22%. Dengan hasil berikut maka diharapkan pula kepada masyarakat untuk bisa mengurangi pemakaian kendaraan bermotor yang dapat menyebabkan pencemaran udara di DKI Jakarta.
Co-Authors Carolus Agung Segara Wisesa Cornelia Antonieta Da Costa Cornelia Antonieta DC Cyntia Larasati Depriansa Fitron