IMPLEMENTASI ALGORITMA K-MEDOIDS UNTUK CLUSTERING WILAYAH TERINFEKSI KASUS COVID-19 DI DKI JAKARTA

Muh Arifandi, Arief Hermawan, Arief Hermawan, Donny Avianto, Donny Avianto

Abstract


In early March 2019, Indonesia was hit by the Covid-19 (Corona) outbreak. The increase in the number of patients infected with the Covid-19 virus is increasing day by day and is already difficult to control. Jakarta is no exception. To prevent the increase in cases of COVID-19, it is necessary to create a cluster or grouping of certain areas (Urban village) based on the number of positive, treated, recovered, died and isolated. This grouping will assist the DKI Jakarta government in providing appropriate handling according to the Urban village pattern. The data that will be used as a research study is the data on the distribution of the status of infected cases of Covid-19 in DKI Jakarta Province on May 20, 2021. The K-Medoids algorithm is a method that can determine a set of clusters among a group of data that is close to an object. Based on the research studies that have been carried out, it can be concluded that in the data mining technique, the total grouping of Covid-19 infected cases based on urban areas in DKI Jakarta Province uses the k-medoids algorithm with three clusters. Cluster 0, cluster 1, cluster 2. The highest Covid-19 infected cases in DKI Jakarta Province are shown in cluster 3 with 31 regions. The results of this grouping research will assist the DKI Jakarta government in providing appropriate handling according to the Urban village pattern. K-Medoids can be implemented using large amounts of data with complex attributes.

Full Text:

PDF

References


Agus, P. (2017). Implementation of Data Mining on Rice Imports by Major Country of Origin Using Algorithm Using K-Means Clustering Method. International Journal Of Artificial Intelligence Research, 1(2), 26–33

Arbin, N., Suhaimi, N. S., Mokhtar, N. Z., & Othman, Z. (2016). Comparative analysis between k-means and k-medoids for statistical clustering. Proceedings - AIMS 2015, 3rd International Conference on Artificial Intelligence, Modelling and Simulation, 117–121. https://doi.org/10.1109/AIMS.2015.82

Darmi, Y. D., & Setiawan, A. (2016). Penerapan Metode Clustering K-Means Dalam Pengelompokan Penjualan Produk. Jurnal Media Infotama, 12(2). https://doi.org/10.37676/jmi.v12i2.418

Nasari, F., & Sianturi, C. J. M. (2016). Penerapan Algoritma K-Means Clustering Untuk Pengelompokkan Penyebaran Diare Di Kabupaten Langkat. CogITo Smart Journal, 2(2), 108. https://doi.org/10.31154/cogito.v2i2.19.108-119

Noviyanto, N. (2020). Penerapan Data Mining dalam Mengelompokkan Jumlah Kematian Penderita COVID-19 Berdasarkan Negara di Benua Asia. Paradigma - Jurnal Komputer Dan Informatika, 22(2), 183–188. https://doi.org/10.31294/p.v22i2.8808

Pulungan Nurliana, suhada, S. D. (2019). Penerapan Algoritma K-Medoids Untuk Mengelompokkan Penduduk. KOMIK (Konferensi Nasional Teknologi Informasi Dan Komputer), 3(1), 329– 334. https://doi.org/10.30865/komik.v3i1.16

Sadewo, M. G., Windarto, A. P., & Wanto, A. (2018). Penerapan Algoritma Clustering Dalam Mengelompokkan Banyaknya Desa/Kelurahan Menurut Upaya Antisipasi/ Mitigasi Bencana Alam Menurut Provinsi Dengan K-Means. KOMIK (Konferensi Nasional Teknologi Informasi Dan Komputer), 2(1). https://doi.org/10.30865/komik.v2i1.943

Sindi, S., Ningse, W. R. O., Sihombing, I. A., Ilmi R.H.Zer, F., & Hartama, D. (2020). Analisis algoritma K-Medoids clustering dalam pengelompokan penyebaran Covid-19 di Indonesia. Jti (Jurnal Teknologi Informasi), 4(1), 166–173

Velmurugan, T., & Santhanam, T. (2010). Computational complexity between K-means and K-medoids clustering algorithms for normal and uniform distributions of data points. Journal of Computer Science, 6(3), 363–368. https://doi.org/10.3844/jcssp.2010.363.368

Wira, B., Budianto, A. E., & Wiguna, A. S. (2019). Implementasi Metode K-Medoids Clustering Untuk Mengetahui Pola Pemilihan Program Studi Mahasiwa Baru Tahun 2018 Di Universitas Kanjuruhan Malang. RAINSTEK : Jurnal Terapan Sains & Teknologi, 1(3), 53–68. https://doi.org/10.21067/jtst.v1i3.3046

Yunus NR, & A, R. (2020). Kebijakan Pemberlakuan Lock Down Sebagai Antisipasi Penyebaran Corona Virus Covid-19. Salam: Jurnal Sosial Dan Budaya Syar-I, 7(3), 227–238. http://journal.uinjkt.ac.id/index.php/salam/article/v iew/15083




DOI: https://doi.org/10.31884/jtt.v7i2.353

Refbacks

  • There are currently no refbacks.


Copyright (c) 2021 JTT (Jurnal Teknologi Terapan)

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

View Stats

 

 Creative Common Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)