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All Journal Jurnal Teknosains Kodepena (Kodepena Journal of Technoscience) Jurnal Teknosains Kodepena (Kodepena Journal of Technoscience) Journal of Informatics and Advanced Computing
MICHAEL SITORUS
Institut Teknologi dan Bisnis Bank Rakyat Indonesia
Computer Science & IT Electrical & Electronics Engineering Energy Engineering Immunology & microbiology Other

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PENERAPAN ALGORITMA K-MEANS PADA CLUSTERING VAKSINASI COVID-19 DAERAH JAWA TIMUR MICHAEL SITORUS; CORNELIA ANTONIETA .DC.; CYNTIA LARASATI
JURNAL TEKNOSAINS KODEPENA Vol. 3 No. 1 (2022): Volume 3 Nomor 1 Agustus 2022
Publisher : Kodepena

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Abstract

Entering the era of the Covid-19 pandemic, the government has intensively implemented a vaccination program to date. The Covid-19 vaccination program is carried out as an effort to boost the immune system, reduce the risk of transmission, reduce the severe impact of the virus, to achieve group immunity. In its own 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.
PENERAPAN ALGORITMA K-MEANS PADA CLUSTERING VAKSINASI COVID-19 DAERAH JAWA TIMUR MICHAEL SITORUS; CORNELIA ANTONIETA .DC.; CYNTIA LARASATI
JURNAL TEKNOSAINS KODEPENA Vol. 3 No. 1 (2022): Volume 3 Nomor 1 Agustus 2022
Publisher : Kodepena

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

Abstract

Entering the era of the Covid-19 pandemic, the government has intensively implemented a vaccination program to date. The Covid-19 vaccination program is carried out as an effort to boost the immune system, reduce the risk of transmission, reduce the severe impact of the virus, to achieve group immunity. In its own 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.
Penerapan Algoritma C4.5 terhadap Pengaruh VSTOCK.ID pada Masyarakat di Masa Pandemi Covid-19 Michael Sitorus; Vanesa
Journal of Informatics and Advanced Computing (JIAC) Vol 2 No 2 (2021): Journal of Informatics and Advanced Computing
Publisher : Teknik Informatika Universitas Pancasila

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The Covid-19 Pandemic Outbreak, is an international disaster that has shaken all aspects of life, including the business world. With the Covid-19 outbreak, automatically there will be no face-to-face meetings to avoid the spread of Covid-19, or at least minimizing meetings. Vstock.id's business problems that arise in society are the way Vstock.id conducts activities to disseminate information to its consumers, because many consumers have doubts about the original brand of a product and service or facility made by Vstock.id and the level of consumer satisfaction during the Covid-19 period. The main goal in establishing Vstock.id is to provide an average price without setting a high price but in accordance with proportional quality such as high quality, original, branded and can be purchased by all groups even though branded products, so that all people can feel the fashion bar brands in the future. now. Vstock.id's business concept is with quality clothing trends, trend brands, quality materials, original brands, and prices that are much cheaper than market store prices. This business conclusion shows that the order of attributes that have the highest level of importance in Vstock.id business development is clothing trends, quality of materials, brand trends, original or original brands and the last is price. The advice that can be given is the development of fashion trends that exist in the following year or now which must be based on the formation of a brand, quality and price to make Vstock.id's business as well as the product ideal. Where the ideal products and businesses that match consumer preferences for the development of Vstock.id are branded or branded goods with original quality such as buying from a store but below the market store selling price with quality control check Product selling price starts from IDR. 80,000 - 300,000.
PENENTUAN STRATEGI PENGEMBANGAN MINAT DAN BAKAT MAHASISWA BRI INSTITUTE DENGAN MEMBUAT CLUSTERING BERDASARKAN HASIL PENILAIAN DECOMPE 1.0 Michael Sitorus; Putriarrum Wardani; Selvianan Tasya
Journal of Informatics and Advanced Computing (JIAC) Vol 3 No 1 (2022): Journal of Informatics and Advanced Computing
Publisher : Teknik Informatika Universitas Pancasila

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Abstract

Clustering analysis merupakan salah satu teknik dalam data mining untuk mengklasifikasikan suatu kelompok objek yang memiliki karakteristik sama. Jumlah kelompok yang dapat diidentifikasi tergantung pada sejumlah data dan jenis dari objeknya.Pengembangan minat dan bakat saat ini sering menjadi hal yang dilakukan oleh mahasiswa di Indonesia.Maka dari itu, untuk membantu mahasiswanya dalam menemukan minat dan bakat mereka tidak jarang kampus mengadakan kegiatan yang dapat membuat mahasiswa mengeksplor kemampuan mereka dengan mengikuti kegiatan pelatihan maupun kompetisi yang diselenggarakan oleh kampus. BRI Institute memiliki banyak kegiatan yang dapat mengeksplor kemampuan mahasiswa salah satunya kegiatan kompetisi yang diselenggarakan untuk mengetahui seberapa besar minat dan bakat mahasiswa dalam membuat sebuah desain UI/UX, kompetisi ini diberi nama DECOMPE 1.0.Adapun, K-Means pada orange data mining adalah salah satu metode clustering data yang dibagi kedalam bentuk satu atau lebih cluster/kelompok yang memiliki karakteristik sama. Clustering data mahasiswa menggunakan metode K- Means, terdiri dari hasil penilaian juri terhadap hasil karya/design UI/UX yang dilombakan dalam kompetisi Decompe 1.0. Penelitian ini menggunakan data mahasiswa peserta lomba Decome 1.0. Kemudian diperoleh kesimpulan bahwa hasil clustering dikategorikan menjadi 3 yaitu Clustering 1 yang merupakan kategori mahasiswa dengan hasil penilaian rendah dari juri,Clustering 2 dimana kategori mahasiswa yang memperoleh hasil penilaian rata-rata (sedang) dan Clustering 3 merupakan kategori mahasiswa yang memperoleh hasil penilaian yang tinggi dari juri.
Co-Authors CORNELIA ANTONIETA .DC. CYNTIA LARASATI Putriarrum Wardani Selvianan Tasya Vanesa