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

Nurhamidah Nurhamidah; Nusyirwan Nusyirwan; Ahmad Faisol

doi:10.24198/jmi.v16.n2.29293.151-157

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

Nurhamidah Nurhamidah, Nusyirwan Nusyirwan, Ahmad Faisol

Abstract

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.

Keywords

forecasting; seasonal time series; Holt-Winters; smoothing method; additive models

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References

Al Qurani, M.A., Satoso, R., and Safitri, D. 2018. Development Of Parameter Estimates in the Exponential Smoothing Holt-Winters Additive Method Using The Golden Section Estimation Method. E-Journal. 7(4): 39-360.

Atalis, C. 2019. Comparison Of The Multiplicative, Additive, and Double Seasonal Holt-Winters Methods for Predicting car sales. E-Journal. 1(1): 89-95.

Gujarati, D.N. and Porter, D.C. 2009. Basic Econometrics. 5^th Edition. McGraw-Hill Irwin, New York.

Kalekar, P. 2004. Time Series Forecasting Using Holt-Winters Exponential Smoothing. Kanwal Rekhi School of Information Technology, India.

Makridakis, S., Wheelwright, S. C., and Mc Gee, V. E. 1999. Methods and Applications of Volume 1. Forecasting Translated by Ir. UntungSusAdriyanto, M.Sc. and Ir. Abdul Basith, M.Sc. Ed. 2nd. Erlangga, Jakarta.

Mulyana. 2004. Textbook of Time Series Analysis. Padjadjaran University, Bandung.

Montgomery, D. C. 2008. Introduction to Time Series Analysis and Forecasting. John Wiley & Sons, New Jersey.

Putra, E.F., Asdi, Y., Maiyastri. 2019. Forecasting Using The Hot-Winter and SARIMA Exponential Smoothing Method (Case Study: Total Fish Production (Tons) In Sibolga City 2000-2017). E-Journal. 8(1): 75-83.

Safitri, T., Dwidayati, N., and Sugiman. 2017. Comparison of Forecasting Using Holt-Winters and Arima's Exponential Smoothing. E-Journal. 6 (1): 49-58.

Santosa, M.A, Kartika, L.A., and Wiyati, R.K. 2019. Comparison of the Holt Winter Additive Method and the Holt Winter Additive Demped Method in Predicting the Number of Students. E-Journal. 5 (1): 93-98.

Santosa, S. 2009. Business Forecasting: Today’s Business Forecasting Method Using MINITAB and SPSS. PT. Elex Media Komputindo, Jakarta.

Supranto, J. 2000. Statistics: Theory and Applications. Ed. 6nd. Erlangga, Jakarta.

Utami, R. and Atmojo.S. 2017. The Implementation of the Tripple Exponential Smoothing Additive Method for Predicting Sales of Office Stationery (ATK) on “X Stationery.” E-Journal. 11 (2): 25-30.

Yusri. 2013. Social Statistics, Applications and Interpretation. Graha Science, Yogyakarta.

Yusuf, F.I. and Anjasari, D.H. 2018. The Triple Exponential Smoothing Holt-Winters Method for Forecasting The Number Of Domestic Tourists In Banyuwangi District. E-Journal. 4 (2): 1-6.

DOI: https://doi.org/10.24198/jmi.v16.n2.29293.151-157