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All Journal Komunikasi Fisika Indonesia Semesta Teknika Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Jurnal Kreativitas PKM Journal of Technomaterial Physics
Arifianto, Fendy
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Agriculture, Biological Sciences & Forestry Astronomy Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Earth & Planetary Sciences Electrical & Electronics Engineering Energy Engineering Health Professions Materials Science & Nanotechnology Medicine & Pharmacology Nursing Physics Public Health

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Journal : Komunikasi Fisika Indonesia

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Evaluation of the Arima-Kalman model in predicting rainfall in Medan City in 2023 using observation data from 2013 – 2022 Lumbantoruan, Alva Josia; Darmawan, Yahya; Munawar, Munawar; Nardi, Nardi; Arifianto, Fendy; Ferdiansyah, Ervan
Indonesian Physics Communication Vol 22, No 1 (2025)
Publisher : Universitas Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31258/jkfi.22.1.15-22

Abstract

This paper aims to evaluate the ARIMA-Kalman model in predicting rainfall in Medan City for the year 2023. The data used are historical observation data of rainfall from 2013 to 2022 that have been tested for stationary and homogeneity, which proved not to require additional correction. The analysis results show that the ARIMA-Kalman model can capture the general pattern of rainfall well, and shows superiority in producing predictions that are closer to the actual data, with a mean absolute error (MAE) value of 54.11, which is lower than the MAE of the ARIMA model which reaches 55.66. Although the ARIMA model has a smaller root mean square error (RMSE) (66.67 compared to 69.75 for ARIMA-Kalman), the ARIMA-Kalman model shows better consistency, especially in capturing significant fluctuations, such as the peak rainfall that occurred in July 2023. Therefore, ARIMA-Kalman is proven to be more accurate and reliable for predicting rainfall in Medan city, making it a better choice to support water resources planning and management.
Empirical orthogonal functions (EOF) analysis of spatial patterns of dominant variability in the Indian Ocean Manik, Willy Bonanja; Darmawan, Yahya; Munawar, Munawar; Nardi, Nardi; Arifianto, Fendy; Ferdiansyah, Ervan
Indonesian Physics Communication Vol 22, No 1 (2025)
Publisher : Universitas Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31258/jkfi.22.1.23-26

Abstract

The Indian Ocean plays a crucial role in the global climate system, particularly in influencing the seasons in Indonesia. Sea surface temperature (SST) variability in the Indian Ocean affects rainfall patterns, extreme events, such as droughts and floods, in Indonesia. This study analyzes SST variability during the dry season (June – July – August, JJA) and rainy season (December – January – February, DJF) using satellite and reanalysis data from 1981 to 2023 with the empirical orthogonal function (EOF) method. The analysis shows that the dominant SST variability pattern during JJA is related to the Indian Ocean dipole (IOD), which influences rainfall and temperature patterns in Indonesia. In DJF, SST variability is more associated with the Asian-Australian monsoon, affecting rainfall patterns and the potential for floods. This research enhances the understanding of climate dynamics in the Indian Ocean and its impact on Indonesia, and it can be used to predict extreme climate events associated with SST variability.
Co-Authors Amri, Sayful Avrionesti, Avrionesti Donni H, Yosafat Ferdiansyah, Ervan Ferdiyansyah, Ervan Giarno Giarno Lumbantoruan, Alva Josia Manik, Willy Bonanja Munawar Munawar Nardi, Nardi Prima, Rajab Ramdhani, Muhammad Zaki Rista Hernandi Virgianto Sudarisman, Maman Veanti, Desak Putu Okta Whibowo, Gani Hesri Yahya Darmawan