Forecasting Seasonal Time Series Data Using The Holt-Winters Exponential Smoothing Method of Additive Models

Forecasting Seasonal Time Series Data Using The Holt-Winters Exponential Smoothing Method of Additive Models

The purpose of this study was to predict seasonal time series data using the Holt-Winters exponential smoothing additive model.  The data used in this study is data on the number of passengers departing at Hasanudin Airport in 2009-2019, the source of the data obtained from the official website of t...

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Bibliographic Details
Main Authors: Nurhamidah Nurhamidah, Nusyirwan Nusyirwan, Ahmad Faisol
Format: Article
Language:Indonesian
Published: Department of Mathematics, FMIPA, Universitas Padjadjaran 2020-12-01
Series:Jurnal Matematika Integratif
Subjects:
forecasting
seasonal time series
holt-winters
smoothing method
additive models
Online Access:http://jurnal.unpad.ac.id/jmi/article/view/29293
Description
Summary:The purpose of this study was to predict seasonal time series data using the Holt-Winters exponential smoothing additive model.  The data used in this study is data on the number of passengers departing at Hasanudin Airport in 2009-2019, the source of the data obtained from the official website of the Central Statistics Agency.  The results showed that the Holt-Winters exponential smoothing method on the passenger's number at Hasanudin Airport in 2009 to 2019 contained trend patterns and seasonal patterns, by first determining the initial values and smoothing parameters that could minimize forecasting errors.
ISSN:1412-6184
2549-9033

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