Grouping of the Second Wave of Covid-19 Infection Areas in East Java Province Using K-Means Clustering

Fadilah Akbar; Edo Leonardo Dekapriyo; Achmad Murtafi Haris; Agoes Moh. Moefad

doi:10.15642/mantik.2022.8.1.53-62

Authors

Fadilah Akbar UIN Sunan Ampel Surabaya
Edo Leonardo Dekapriyo UIN Sunan Ampel Surabaya, Surabaya, Indonesia
Achmad Murtafi Haris UIN Sunan Ampel Surabaya, Surabaya, Indonesia
Agoes Moh. Moefad UIN Sunan Ampel Surabaya, Surabaya, Indonesia

DOI:

https://doi.org/10.15642/mantik.2022.8.1.53-62

Keywords:

Covid-19, K-Means Clustering, Grouping, East Java, Infection Areas

Abstract

The second wave of Covid-19 Pandemic Attacks that occurred in June 2021 resulted in a drastic number of fatalities. This is due to reduced community responsibility, a sense of caring for each other, and a sense of mutual protection, resulting in the loosening of the health protocols implemented. There needs to be proper mitigation to handle the Covid-19 pandemic properly, one of which is by handling cases in each region with a low level of severity. With this grouping, it can provide a decision on which areas must be available in mitigating the Covid-19 pandemic. For grouping each region, the K-Means Clustering method can be used. From these clusters, there is one area with a severity level, eight areas with moderate severity, and 29 areas with low severity.

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References

H. Ritchie et al., “Coronavirus Pandemic (COVID-19),” OurWorLdInData.org., 2021. https://ourworldindata.org/coronavirus-data (accessed Jul. 23, 2021).

S. T. P. Covid-19, “Peta Sebaran Provinsi Jawa Timur,” Covid19.go.id, 2021. https://covid19.go.id/peta-sebaran (accessed Jul. 23, 2021).

“Pakar: Indonesia Menuju Puncak Gelombang Kedua Corona,” CNN Indonesia, Jakarta, Jun. 21, 2021.

S. T. P. Covid-19, “Peta Sebaran Nasional Per-Provinsi,” Covid19.go.id, 2021. https://covid19.go.id/peta-sebaran (accessed Jul. 24, 2021).

F. R. Makarim, “Gelombang Kedua COVID-19 Berpotensi Terjadi di RI, Apa Sebabnya?,” halodoc, 2021. https://www.halodoc.com/artikel/gelombang-kedua-covid-19-berpotensi-terjadi-di-ri-apa-sebabnya (accessed Jul. 23, 2021).

E. Parwanto, “Virus Corona (SARS-CoV-2) penyebab COVID-19 kini telah bermutasi,” J. Biomedika dan Kesehat., vol. 4, no. 2, pp. 47–49, 2021, doi: 10.18051/jbiomedkes.2021.v4.47-49.

I. Safutra, “PPKM Darurat Batasi Aktivitas Masyarakat di Jawa-Bali,” Jawa Pos, Surabaya, Jul. 02, 2021.

A. Faizal, “Surabaya Jadi Zona Hitam, Apa yang Terjadi?,” Kompas, Surabaya, Jun. 02, 2020.

A. Solichin and K. Khairunnisa, “Klasterisasi Persebaran Virus Corona (Covid-19) Di DKI Jakarta Menggunakan Metode K-Means,” Fountain Informatics J., vol. 5, no. 2, p. 52, 2020, doi: 10.21111/fij.v5i2.4905.

R. A. Indraputra and R. Fitriana, “K-Means Clustering Data COVID-19,” J. Tek. Ind., vol. 10, no. 3, pp. 275–282, 2020.

A. S. Ahmar, D. Napitupulu, R. Rahim, R. Hidayat, Y. Sonatha, and M. Azmi, “Using K-Means Clustering to Cluster Provinces in Indonesia,” J. Phys. Conf. Ser., vol. 1028, no. 1, 2018, DOI: 10.1088/1742-6596/1028/1/012006.

M. Azarafza, M. Azarafza, and H. Akgün, “Clustering method for spread pattern analysis of corona-virus (COVID-19) infection in Iran,” J. Appl. Sci. Eng. Technol. Educ., vol. 3, no. 1, pp. 1–6, 2021, DOI: 10.1101/2020.05.22.20109942.

M. C. Untoro, L. Anggraini, M. Andini, H. Retnosari, and M. A. Nasrulloh, “Penerapan metode k-means clustering data COVID-19 di Provinsi Jakarta,” Teknologi, vol. 11, no. 2, pp. 59–68, 2021, doi: 10.26594/teknologi.v11i2.2323.

J. Hutagalung, N. L. W. S. R. Ginantra, G. W. Bhawika, W. G. S. Parwita, A. Wanto, and P. D. Panjaitan, “COVID-19 Cases and Deaths in Southeast Asia Clustering using K-Means Algorithm,” J. Phys. Conf. Ser., vol. 1783, no. 1, 2021, DOI: 10.1088/1742-6596/1783/1/012027.

S. Harini, “Identification COVID-19 Cases in Indonesia with The Double Exponential Smoothing Method,” J. Mat. Mantik, vol. 6, no. 1, pp. 66–75, 2020, DOI: https://doi.org/10.15642/mantik.2020.6.1.66-75.

M. A. Ramadhan, Efendi, “Perbandingan K-Means dan Fuzzy C-Means untuk Pengelompokan Data User Knowledge Modeling,” in Seminar Nasional Teknologi Informasi, Komunikasi dan Industri (SNTIKI) 9, 2017, pp. 219–226.

A. Chusyairi and P. R. N. Saputra, “Perbandingan Algoritma Fuzzy C-Means Dan K- Means Clustering Dalam Pengelompokan Data Puskesmas,” in Conference on Information Technology, Information System and Electrical Engineering (CITISEE 2019), 2019, no. June, pp. 1–6.

A. Bastian, H. Sujadi, and G. Febrianto, “Penerapan Algoritma K-Means Clustering Analysis Pada Penyakit Menular Manusia (Studi Kasus Kabupaten Majalengka),” J. Sist. Inf., vol. 14, no. 1, pp. 26–32, 2018.

M. Zubair, M. Asif Iqbal, A. Shil, E. Haque, M. Moshiul Hoque, and I. H. Sarker, “An Efficient K-Means Clustering Algorithm for Analysing COVID-19,” Adv. Intell. Syst. Comput., vol. 1375 AIST, pp. 422–432, 2021, DOI: 10.1007/978-3-030-73050-5_43.

M. Fajar, “Modeling of COVID-19 Epidemic Growth Curve in Indonesia,” J. Mat. Mantik, vol. 7, no. 1, pp. 67–73, 2021, doi: https://doi.org/10.15642/mantik.2021.7.1.67-73.

D. Abdullah, S. Susilo, A. S. Ahmar, R. Rusli, and R. Hidayat, “The application of K-means clustering for province clustering in Indonesia of the risk of the COVID-19 pandemic based on COVID-19 data,” J. Qual. Quant., no. 0123456789, 2021, DOI: 10.1007/s11135-021-01176-w.

D. N. Sari and I. Yunita, “Tingkat Keparahan Dan Risiko Penyebaran Covid-19 Di Indonesia Dengan Menggunakan K-Means Clustering,” in Seminar Nasional Official Statistics, 2019, pp. 210–216, doi: 10.34123/semnasoffstat.v2020i1.706.

F. Virgantari and Y. E. Faridhan, “K-Means Clustering of COVID-19 Cases in Indonesia ’ s Provinces,” in Proceedings of the International Conference on Global Optimization and Its Applications Jakarta, 2020, pp. 1–7.

A. Mahmudan, “Clustering of District or City in Central Java Based COVID-19 Case Using K-Means Clustering,” J. Mat. Stat. dan Komputasi, vol. 17, no. 1, pp. 1–13, 2020, doi: 10.20956/jmsk.v17i1.10727.

A. Ali, “Klasterisasi Data Rekam Medis Pasien Menggunakan Metode K-Means Clustering di Rumah Sakit Anwar Medika Balong Bendo Sidoarjo,” MATRIK J. Manajemen, Tek. Inform. dan Rekayasa Komput., vol. 19, no. 1, pp. 186–195, 2019, doi: 10.30812/matrik.v19i1.529.

M. S. Yana, L. Setiawan, E. M. Ulfa, and A. Rusyana, “Penerapan Metode K-Means dalam Pengelompokan Wilayah Menurut Intensitas Kejadian Bencana Alam di Indonesia Tahun 2013-2018,” J. Data Anal., vol. 1, no. 2, pp. 93–102, 2018, doi: 10.24815/jda.v1i2.12584.