Comparative Study of Concepts and Implementation of Various Univariate Time Series Analysis Methods

Indonesian Journal of Computing and Modeling

View Publication Info
 
 
Field Value
 
Title Comparative Study of Concepts and Implementation of Various Univariate Time Series Analysis Methods
 
Creator Nugroho, Adi
 
Description Univariate time series analysis is a very important method in everyday life because this method has many practical applications. Various methods of time series analysis have been previously discovered by experts. However, until now the experts have not been able to determine exactly which method is best implemented in certain time series data. In this paper we will make a comparison of the 8 (eight) time series analysis methods that are most often used, namely SMA, EMA, WMA, SES, Holt's Method, Holt's Winter Seasonal Method, ARIMA, and SARIMA, with the aim of providing guidance to readers to choose which method is most appropriate for a given time series data. Research for this was conducted using the same data for all methods.
 
Publisher Pusat Studi Sistem Informasi dan Pemodelan Mitigasi Tropika
 
Date 2021-03-02
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Identifier https://ejournal.uksw.edu/icm/article/view/4594
 
Source Indonesian Journal of Computing and Modeling; Vol 3 No 2 (2020)
2598-9421
 

Contact Us

The PKP Index is an initiative of the Public Knowledge Project.

For PKP Publishing Services please use the PKP|PS contact form.

For support with PKP software we encourage users to consult our wiki for documentation and search our support forums.

For any other correspondence feel free to contact us using the PKP contact form.

Find Us

Twitter

Copyright © 2015-2018 Simon Fraser University Library