Prediction of the Number of New Cases of Covid-19 in Indonesia Using Fuzzy Time Series Model Chen

Kanda Januar Miraswan, Wiwik Anum Puspita, Alvi Syahrini Utami

Abstract

Coronavirus Diseases 2019 (Covid-19) is a disease caused by a virus that originated in Wuhan, China. This virus infects people rapidly to the country of Indonesia. According to the latest Covid-19 Development Team in Indonesia, as of 09/08/2021, there were around 3,686,740 people who were confirmed positive for Covid-19. With the numbers continuing to grow, predictions of new cases of Covid-19 in Indonesia were made using the time series method. The method used by the researcher is Chen's Fuzzy Time Series. The purpose of the researcher is to forecast, to find out the prediction of the number of new cases of Covid-19 in Indonesia using the FTS Chen method into software. In addition, in order to provide information to predict, so that the government knows and can make decisions. To measure the performance of the method, the Mean Absolute Percentage Error (MAPE) is used as a measure of the level of accuracy of the forecasting performed. The test data used were 363 data with several variations of parameters  & . From the results of the analysis that was tested by the researcher, with 50 trials of parameter input, better accuracy results were obtained at input  = 135135 and  = 2000 with MAPE is 35.55006797 (35%).

Full Text:

PDF

References

Junaedi, D., & Salistia, F. (2020). Dampak Pandemi Covid-19 Terhadap Pasar Modal Di Indonesia: Al-Kharaj : Jurnal Ekonomi, Keuangan & Bisnis Syariah, 2(2), 109–138. https://doi.org/10.47467/alkharaj.v2i2.112

Agung, I. M. (2020). Memahami Pandemi Covid-19 Dalam Perspektif Psikologi Sosial. Psikobuletin:Buletin Ilmiah Psikologi, 1(2), 68–84. http://ejournal.uinsuska.ac.id/ndex.php/Psikobuletin/article/view/9616/5058

Ella, A. P., & Arifianto, D. (2020). Penerapan Fuzzy Time Series dalam Peramalan Harga Minyak Serai pada CV Agam Jaya Atsiri. 1–8.K. Elissa, “Title of paper if known,” unpublished.

Nugroho, K. (2016). Model Analisis Prediksi Menggunakan Metode Fuzzy Time Series.Infokam,12(1),46–50. http://amikjtc.com/jurnal/index.php/jurnal/article/view/91

Vivianti, V., Aidid, M. K., & Nusrang, M. (2020). Implementasi Metode Fuzzy Time Series untuk Peramalan Jumlah Pengunjung di Benteng Fort Rotterdam. 2(1), 1–12.

https://doi.org/10.35580/variansiunm12895.

Febriana, E. T. (2018). Fuzzy Time Series Chen Orde Tinggi Untuk Meramalkan Jumah Penumpang Dan Kendaraan Kapal (Studi Kasus: PT ASDP Indonseia Ferry (Persero) Cabang Merak). Universitas Islam Indonesia, Yogyakarta.

Saelan, A. (2009). Logika Fuzzy. Struktur Diskrit, 1(13508029), 1–5.

Ade Putra, N., Kurniawan, H., & Ritha, N. (2017). Prediksi Jumlah Penduduk Menggunakan Fuzzy Time Series Model Chen (Studi Kasus: Kota Tanjungpinang). Journal of Chemical Information and Modeling, 53(9), 1689–1699.J. Clerk Maxwell, A Treatise on Electricity and Magnetism, 3rd ed., vol. 2. Oxford: Clarendon, 1892, pp.68–73.

Fauziah, N., Wahyuningsih, S., & Nasution, Y. N. (2016). Peramalan Menggunakan Fuzzy Time Series Chen (Studi Kasus : Curah Hujan Kota Samarinda). 4(2).

Perwitasari, R., Afwani, R., & Endang Anjarwani, S. (2020). Penerapan Metode Rational Unified Process (RUP) dalam Pengembangan Sistem Informasi Medical Check Up pada Citra Medical Centre (The Application of RationalUnifiedProcess(RUP)) in Development of a Medical. 2(1), 76–88.

DOI: https://doi.org/10.36706/sjia.v3i1.35

Refbacks

  • There are currently no refbacks.