Metode Fuzzy Time Series Model Chen Untuk Memprediksi Jumlah Kasus Aktif Covid-19 Di Indonesia

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.

Analisis dan Peramalan Polusi Udara di Surabaya Menggunakan Metode Fuzzy Time Series

“…Dengan demikian, tujuan dari penelitian ini adalah untuk menerapkan pendekatan inovatif, yakni metode Fuzzy Time Series. Fuzzy Time Series mengintegrasikan konsep fuzzy logic dengan metode analisis deret waktu, memungkinkan membuat model yang disesuaikan dengan kompleksitas dan ketidakpastian data deret waktu tentang polusi udara [1]. Memahami sifat perubahan dan faktor-faktor yang mempengaruhinya, direncanakan akan dibuat model peramalan yang akurat dan efektif yang akan memberikan informasi terkini tentang polusi udara di Surabaya.…”