Analisis Cluster Untuk Pemetaan Data Kasus Covid-19 di Indonesia Menggunakan K-Means

Authors

  • Nurissaidah Ulinnuha
  • Siti Azizatus Sholihah

DOI:

https://doi.org/10.24252/msa.v9i2.19478

Abstract

Indonesia merupakan salah satu negara yang terjangkit virus Covid - 19. Covid - 19 merupakan penyakit yang dapat menular yang ditandai dengan gejala pada bagian pernapasan. Oleh karena itu, di masa pandemi ini sangat penting untuk menghindari wilayah dengan persebaran Covid - 19 yang tinggi. Pada Penelitian ini dilakukan clustering penyebaran kasus Covid - 19 di Indonesia dengan menerapkan metode data mining. Pengelompokan dilakukan berdasarkan parameter jumlah pasien positif, sembuh, meninggal, suspect, probable, dan negatif. Salah satu cara untuk melihat perkembangan kasus Covid - 19 di Indonesia dapat menggunakan algoritma K - Means yang mengunakan beberapa kelompok. Data - data tanpa label kelas diterima oleh algoritma K - Means ini. Penelitian ini menggunakan algoritma K - Means untuk menentukan bagaimana tingkat penyebaran Covid - 19 di setiap Provinsi di Indonesia. Validasi silhouette index (SI) digunakan untuk menentukan cluster optimal. Hasil penelitian menunjukkan bahwa cluster optimal terletak pada k = 2 dengan nilai SC = 0,74 yang menunjukkan bahwa struktur cluster termasuk kuat. Berdasarkan hasil cluster optimal, didapat 2 kelompok yaitu kelompok rawan yang terdiri dari Provinsi Banten, DKI Jakarta, Jawa Barat, Jawa Tengah, Jawa Timur, dan Riau, dan terakhir kelompok aman yang terdiri dari 28 provinsi lainnya.

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Published

2021-12-28

How to Cite

[1]
N. Ulinnuha and S. A. Sholihah, “Analisis Cluster Untuk Pemetaan Data Kasus Covid-19 di Indonesia Menggunakan K-Means”, MSA, vol. 9, no. 2, pp. 27–31, Dec. 2021.

Issue

Vol. 9 No. 2 (2021): VOLUME 9 NOMOR 2 TAHUN 2021

Section

Artikel

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