Proceedings of the Mathematics and Science Education International Seminar 2021 (MASEIS 2021)

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Prediction Farmer Exchange Rate Comparative Method of Analysis Holth-Winters Smoothing and Seasonal ARIMA

Authors
Harizahayu1, *, Amin Harahap2, Muhammad Fathoni3, Hari Sumardi4
1Management Informatics Study Program, Politeknik Negeri Medan, Medan, Indonesia
2Mathematics Education Study Program, Universitas Labuhan Batu, Labuhan Batu, Indonesia
3Management Informatics Study Program, Kampus Politeknik Unggulan LP3M, Medan, Indonesia
4Mathematics Education Study Program, University of Bengkulu, Bengkulu, Indonesia
*Corresponding author. Email: harizahayu@polmed.ac.id
Corresponding Author
Harizahayu
Available Online 29 March 2023.
DOI
10.2991/978-2-38476-012-1_15How to use a DOI?
Keywords
Forecasting; Holt-Winters Exponential Smoothing; Seasonal Arima; Best Model
Abstract

The purpose of this research was to predict seasonal time series data using the Holt-Winters exponential smoothing additive model and the Seasonal autoregressive integrated moving average (ARIMA). The data used in this study is data on farmer term of trade at Nort Sumatera in 2016–2020, the source of the data obtained from thes Social website of the Central Statistics Agency. The comparison of the Holt-Winters exponential smoothing method and SARIMA on farmer term of trade from 2016 to 2020 revealed trend patterns and seasonal patterns by first determining the initial values and smoothing parameters to minimize forecasting errors and obtain forecasting from the best model. The best model to prec farmer term of trade is SARIMA (2, 1, 1) 0, 1, 112 because the model fits the observed data well and shows no residual autocorrelation. The results of forecasting farmer term of trade at Nort Sumatera in 2016–2020 have increased continuously every month.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the Mathematics and Science Education International Seminar 2021 (MASEIS 2021)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
29 March 2023
ISBN
978-2-38476-012-1
ISSN
2352-5398
DOI
10.2991/978-2-38476-012-1_15How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Harizahayu
AU  - Amin Harahap
AU  - Muhammad Fathoni
AU  - Hari Sumardi
PY  - 2023
DA  - 2023/03/29
TI  - Prediction Farmer Exchange Rate Comparative Method of Analysis Holth-Winters Smoothing and Seasonal ARIMA
BT  - Proceedings of the Mathematics and Science Education International Seminar 2021 (MASEIS 2021)
PB  - Atlantis Press
SP  - 107
EP  - 116
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-012-1_15
DO  - 10.2991/978-2-38476-012-1_15
ID  - 2023
ER  -