Transformasi
Vol 18, No 1 (2022): TRANSFORMASI

METODE FUZZY TIME SERIES MODEL CHEN UNTUK MEMPREDIKSI JUMLAH KASUS AKTIF COVID-19 DI INDONESIA

Arif Ikhsanudin (STMIK Bina Patria)
Kartika Imam Santoso (STMIK Bina Patria)
Sugeng Wahyudion0 (STMIK Bina Patria)



Article Info

Publish Date
23 Jun 2022

Abstract

In 2021, new cases of COVID-19 continue to be increase in Indonesia every day, so this pandemic can be said to be still not over. Estimates of the number of active cases in the next day can be used to make policies, as far as prepare stocks of medical equipment needs. This study presents the use of the Chen model Fuzzy Time Series to predict the number of active COVID-19 cases in Indonesia in the next one day based on data from the past 30 days. Official government data is used as actual data to calculate predicted results. The results of this study show that in the range of 30 days from July 19, 2021, to August 17, 2021, using the Chen model Fuzzy Time Series method to predict the number of active COVID-19 cases in Indonesia, forecasting on 18 August 2021 with cases of 376,339 with an error ratio MAPE of 3.53% which is included in the category of very good forecasting.

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Journal Info

Abbrev

JT

Publisher

Subject

Computer Science & IT Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Mathematics

Description

Jurnal transformasi sebagai wadah untuk mengembangkan Dan mensosialosasikan IPTEk berbasis penelitian dan kajian ilmiah (artikel review) dalam lingkup Informatika, elektronika, manajemen, pendidikan & ...