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PENGGUNAAN METODE DOUBLE EXPONENTIAL SMOOTHING TIPE HOLT PADA PERAMALAN KASUS COVID-19 DI PROVINSI SUMATERA SELATAN

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Penilaian

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Holt Type Double Exponential Smoothing Method can be used for trending data. This method uses two parameters, the parameters are exponential smoothing value parameter and the trend value smoothing parameter. COVID-19 data grows exponentially and has distribution model follow to Double Exponential Smoothing model. The purpose of this study are to obtain forecasting model and forecasting results from COVID-19 data cases. This study uses COVID-19 data cases on period 01 January 2021 – 28 February 2022, which is 424 days. The result of this research obtained forecasting models for five categories of COVID-19, namely Discarded Close Contacts, Asymptomatic Cases, Symptomatic Cases, Death Confirmation, and Recovered Confirmation. The five forecasting models are used to determine total of COVID-19 data cases on 425th day period onwards. The forecast error size of model is determined based on MAPE (Mean Absolute Percentage Error) value with obtained MAPE values for all categories are lower than 10%, which means that forecasting models has a very good performance for forecasting COVID-19 data cases.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2207002941	T72336	T723362022	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T723362022

Publisher

Inderalaya : Jurusan Matematika, Fakultas Matematika Dan Ilmu Pengetahuan Alam Universitas Sriwijaya., 2022

Collation

xv, 85 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

519.507

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Jurusan Matematika
Matematika Statistikal

Specific Detail Info

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Statement of Responsibility

SEPTA

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