Analisis Rantai Markov dalam Memprediksi Status Pasien COVID-19 di Indonesia

  • Nabila Nurita Putri Program Studi Matematika Institut Teknologi Sumatera, Lampung Selatan, 35365, Indonesia
  • Triyana Muliawati Program Studi Matematika Institut Teknologi Sumatera, Lampung Selatan, 35365, Indonesia

Abstract

COVID-19 is an infectious disease caused by a new type of corona virus, beta coronavirus. The spread of COVID-19 can occur through human interactions. On March 9, 2020 the WHO (World Health Organization) officially declared COVID-19 a pandemic. This means that COVID-19 has spread widely in the world. Until now, there has not been found a drug to treat COVID-19. So, it is necessary to predict when the COVID-19 pandemic will end. This study discusses the Markov chain method in predicting the status of COVID-19 patients in Indonesia. The prediction of the number of people who are positive for COVID-19, recovered, and die can be one of the government's bases for determining when the large-scale social restrictions (PSBB) will end. The results of the study stated that the COVID-19 pandemic in Indonesia would end at the end of 2020. On December 5, 2020 there were no more people infected with COVID-19 with a cure rate of 29.815% of patients with COVID-19 and a death rate of 3, 5933%.

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References

[1] J. Bird, Matematika Dasar: Teori dan Aplikasi Praktis Edisi Ketiga. Jakarta: Erlangga, 2004.
[2] Darmawan Giri, dkk., ”Kajian Persaingan di Dalam Pasar Industrial Menggunakan Rantai Markov,” TMI, vol. 2, pp. 89 – 102, April 2002.
[3] F. S. Hiller dan G.J. Lieberman, Introduction to Operations Research. McGraw Hill, 2001.
[4] H. M. Taylor dan S. Karlin, An Introduction to Stochastic Modeling Third Edition. Oxford: Academic Press, 1998.
[5] Muhammad Arif Tiro, dkk., Dasar-Dasar Statistika: Edisi Ketiga. Makassar: Universitas Negeri Makasar Press, 2008.
[6] Muhammad Arif Tiro. Pengantar Teori Peluang. Makassar: Universitas Makassar Press, 2008.
[7] S. A. Pramuditya, R. Marwati dan E. Puspita, “Peramalan Pangsa Pasar Kartu GSM dengan Pendekatan Rantai Markov,” Euclid, vol. 1, pp. 116 – 124, 2014.
[8] Purwanto, “Virus Corona (2019-nCoV) Penyebab COVID-19,” Jurnal Biomedika dan Kesehatan, vol. 3, pp. 1-2, 2020.
[9] A. Susilo, Coronavirus Disease 2019: Tinjauan Literatur Terkini. Jakarta: RSUPN Dr. Cipto Mangunkusumo, 2020.
[10] Djini Tamudia, dkk., “Analisis Rantai Markov untuk Memprediksi Perpindahan Merek Shampoo di Hypermart Swalayan Manado Town Square”. Jurnal Matematika dan Aplikasi, vol. 3, no. 1., pp. 58 – 65, 2014.
[11] Yuliana, “Corona Virus Disease (Covid-19),” Wellness and Healthy Magazine, vol. 2, pp. 187-192, 2020.
[12] Nurfitrianti, “Penerapan Data Mining untuk Memprediksi Harga Beras di Indonesia Menggunakan Model Markov,” Skripsi thesis Universitas Islam Negeri Sultan Syarif Kasim, Pekanbaru Riau, 2019.
[13] D. Saputra, “Penggunaan Rantai Markov pada Perhitungan Persediaan Barang Menggunakan Peluang Steady State,” Universitas Negeri Lampung, Bandar Lampung, 2018
Published
2021-05-10
How to Cite
PUTRI, Nabila Nurita; MULIAWATI, Triyana. Analisis Rantai Markov dalam Memprediksi Status Pasien COVID-19 di Indonesia. Indonesian Journal of Applied Mathematics, [S.l.], v. 1, n. 2, p. 44-50, may 2021. ISSN 2774-2016. Available at: <https://journal.itera.ac.id/index.php/indojam/article/view/352>. Date accessed: 16 june 2021. doi: https://doi.org/10.35472/indojam.v1i2.352.