# Decomposition Method with Application of Grey Model GM(1,1) for Forecasting Seasonal Time Series
> Hikmah N.

URL kanonis: https://discover.unhas.ac.id/publications/pub_scopus_85131423182
Jurnal / Konferensi: Pakistan Journal of Statistics and Operation Research
Tahun terbit: 2022
DOI: https://doi.org/10.18187/pjsor.v18i2.3533
ISSN: 18162711
Kuartil SJR: Q2
Citations: 4

## Authors
- Hikmah N.

## Abstract
Forecasting is one of the activities needed by companies to determine the policies that need to be taken for the continuity of operations. There are many methods for forecasting, one of which is the grey model GM(1,1). The GM(1,1) is one of the successful forecasting methods applied to economics, finance, engineering, and others. However, according to several previous study, the GM(1,1) is not good enough to forecast data containing seasonal characteristics. Therefore, the aim of this study is to develop hybrid model so that the GM(1,1) is able to forecast seasonal time series. The hybrid model is constructed by combining decomposition method for seasonality adjustment and grey model GM(1,1) for forecasting seasonal time series. The results are compared to seasonal grey model SGM(1,1). Based on the evaluation using error criteria, it is found that the hybrid model is the best model.

## Keywords
- Seasonality
- Series (stratigraphy)
- Seasonal adjustment
- Decomposition
- Econometrics
- Mathematics
- Time series
- Statistics
- Ecology
- Paleontology
- Mathematical analysis
- Variable (mathematics)
- Biology

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Sumber: Discover Unhas — RIMS Universitas Hasanuddin.
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