Version 1
: Received: 28 April 2022 / Approved: 29 April 2022 / Online: 29 April 2022 (08:44:28 CEST)
How to cite:
Natayu, A.; Clarke, Q.J.H.; Fikri, M. Benchmark of Holt-Winters and SARIMA Methods in Predicting Jakarta Climate. Preprints2022, 2022040295. https://doi.org/10.20944/preprints202204.0295.v1
Natayu, A.; Clarke, Q.J.H.; Fikri, M. Benchmark of Holt-Winters and SARIMA Methods in Predicting Jakarta Climate. Preprints 2022, 2022040295. https://doi.org/10.20944/preprints202204.0295.v1
Natayu, A.; Clarke, Q.J.H.; Fikri, M. Benchmark of Holt-Winters and SARIMA Methods in Predicting Jakarta Climate. Preprints2022, 2022040295. https://doi.org/10.20944/preprints202204.0295.v1
APA Style
Natayu, A., Clarke, Q.J.H., & Fikri, M. (2022). Benchmark of Holt-Winters and SARIMA Methods in Predicting Jakarta Climate. Preprints. https://doi.org/10.20944/preprints202204.0295.v1
Chicago/Turabian Style
Natayu, A., Quincy Julian H. Clarke and Muhamad Fikri. 2022 "Benchmark of Holt-Winters and SARIMA Methods in Predicting Jakarta Climate" Preprints. https://doi.org/10.20944/preprints202204.0295.v1
Abstract
As its capital, Jakarta plays a critical role in boosting Indonesia’s economic growth and setting the precedent for broader change outside of the city. One crucial avenue of inquiry to better understand, and prepare for, the future of a country so heavily impacted by disastrous weather events is understanding the effects of climate change through data. This study investigates meteorological data collected from 1996 to 2021 and compares the application of the SARIMA and the Holt-Winters methods to predict the future influence of climatic parameters on Jakarta’s weather. The performance of the SARIMA method is proven to provide better results than the Holt-Winter models and both methods showed the best performances when forecasting the humidity data. The results of the forecast are able to demonstrate the characteristic of the climate in Jakarta, with dry season ranging from May to October and wet season ranging from November to April.
Keywords
Forecasting; SARIMA; Holt-Winters; Climate; Big Data
Subject
Computer Science and Mathematics, Probability and Statistics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
