Cluster Analysis of Covid-19 Distribution Using K-Means Clustering Algorithm
Case Study: West Java Province
Abstract
Coronavirus disease (covid-19) has become a global concern after on January 20, 2020, three people were killed in the city of Wuhan, Hubei province, China. Covid-19 was first reported to have entered Indonesia on March 2, 2020, with two cases. This study aims to conduct a cluster analysis of the distribution of COVID-19 cases in West Java province as of April 1, 2021 with the variables of isolation, recovery, and death. By using the elbow method, the difference in SSE in each cluster, the silhouette graph, and the factoextra diagram, the optimum number of clusters is 3, the evaluation results show the Dunn index value = 0.4776, connectivity = 9.4738, and silhouette = 0.5839 (data structure reasoned). The clustering results show a good variance of 75.8%. Cluster 1 consists of 1 city/district, cluster 2 consists of 6 cities/districts, and cluster 3 consists of 20 cities/districts.
References
Dwitri, N., Tampubolon, J.A., Prayoga, S., Zer, F. I. R. H., & Hartama, D. (2020). Penerapan Algoritma K-Means Clustering Dalam Menentukan Tingkat Penyebaran Pandemi Covid-19 Di Indonesia. Jurnal Teknologi Informasi, 4(1): 128-132.
Hertina, H., Nurwahid, M., Haswir, H., Sayuti, H., Darwis, A., Rahman, M., ... & Hamzah, M. L. (2021). Data mining applied about polygamy using sentiment analysis on Twitters in Indonesian perception. Bulletin of Electrical Engineering and Informatics, 10(4), 2231-2236.
Khotimah, T., & Darsin. (2020). Clustering Perkembangan Kasus Covid-19 Di Indonesia Menggunakan Self Organizing Map. Jurnal Dialektika Informatika (Detika), 1(1): 23-26.
Liu, J., Kantarci, B., & Adams, C. (2020, July). Machine learning-driven intrusion detection for Contiki-NG-based IoT networks exposed to NSL-KDD dataset. In Proceedings of the 2nd ACM Workshop on Wireless Security and Machine Learning (pp. 25-30).
Mardi, Y. (2016). Data Mining: Klasifikasi Menggunakan Algoritma C4.5. Jurnal Edik Informatika, 2(2): 213-219.
Riedel, S., Morse, S., Mietzner, T., Miler, S. J., Melnick., & Adelberg's Medical Microbiology. (2019). Adelberg's Medical Microbiology (28thed.). New York: McGraw-Hill Education/Medical.
Sinaga, K. P., & Yang, M. S. (2020). Unsupervised K-means clustering algorithm. IEEE Access, 8, 80716-80727.
Sindi, S., Ningse, W. R. O., Sihombing, I. A., Ilmi, F., & Hartama, D. (2020). Analisis Algoritma K-Medoids Clustering Dalam Pengelompokan Penyebaran Covid-19 Di Indonesia. Jurnal Teknologi Informasi, 4(1): 166-173.
Plotnikova, V., Dumas, M., & Milani, F. (2020). Adaptations of data mining methodologies: a systematic literature review. PeerJ Computer Science, 6, e267.
Yogi Yunefri, Nizwardi Jalinus, Syahril, Muhammad Luthfi Hamzah. (2020). Grouping Systems In Cooperative Oriented Problem Learning Model Using K-Means Clustering. International Journal of Advanced Science and Technology, 29(05), 5963 - 5971. Retrieved from http://sersc.org/journals/index.php/IJAST/article/view/15570