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All Journal Indonesian Journal of Applied Statistics Navigation Physics : Journal of Physics Education
Aslam, Fadhil Muhammad
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Agriculture, Biological Sciences & Forestry Computer Science & IT Earth & Planetary Sciences Economics, Econometrics & Finance Education Environmental Science Physics Other

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Analisis Dinamika Atmosfer Saat Peristiwa Siklon Tropis Paddy di Pulau Jawa Aslam, Fadhil Muhammad
Navigation Physics : Journal of Physics Education Vol 6, No 2 (2024): Navigation Physics : Journal of Physics Education Vol. 6 No. 2 Tahun 2024
Publisher : UNIVERSITAS INDRAPRASTA PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/npjpe.v6i2.2743

Abstract

Java Island is the most densely populated island in Indonesia. Consequently, Java Island is also prone to atmospheric disturbances that affect the activities of its inhabitants. One such event was Tropical Cyclone Paddy, which occurred from November 22 to 24, 2021. The aim of this study is to understand and delve into the analysis of atmospheric dynamics during the Tropical Cyclone Paddy event, which subsequently impacts the lives and activities of the people on Java Island. This study utilizes data from various meteorological parameters such as rainfall, zonal and meridional winds, sea surface temperature (SST), humidity, and pressure collected from several sources, namely: Himawari-8 Satellite, GsMap, ECMWF Era 5 hourly data on pressure levels, and NOAA. The research examines the dynamics of sea surface temperature (SST) anomalies, wind patterns, lower-level moisture transport (LLMT), divergence, surface pressure, and rainfall during the Tropical Cyclone Paddy event. Software such as GrADS 2.2 and Python were used for spatial analysis. The analysis indicates that high SST anomalies, convergence, and high LLMT contributed to the formation of convective clouds, ultimately resulting in high rainfall in the southern regions of Java affected by the cyclone. Over time, there was a decline in these phenomena, marked by a decrease in pressure, wind speed, and rainfall, leading to the normalization of weather conditions in Java Island post-cyclone.
Comparing Monthly Rainfall Prediction in West Sumatra Using SARIMA, ETS, LSTM, and XGBoosting Methods Aslam, Fadhil Muhammad; Afghani, Fadhli Aslama
Indonesian Journal of Applied Statistics Vol 7, No 1 (2024)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v7i1.83187

Abstract

The West Sumatra Province, serving as the trading center on the island of Sumatra, and boasting various attractive tourist destinations, is not immune to incidents of high precipitation leading to hydro-meteorological disasters such as floods and landslides. Therefore, the accurate prediction of monthly rainfall is crucial to minimize the impacts of high precipitation. This research aims to determine the best method for predicting monthly rainfall using data from 1992 to 2022, which can adequately represent its climatological conditions. The results indicate that the Extreme Gradient Boosting method outperforms the Seasonal Autoregressive Integrated Moving Average (SARIMA), Exponential Smoothing (ETS), and Long Short-Term Memory (LSTM) methods in West Sumatra Province, represented by three weather observation points from the BMKG (Climatology Station of West Sumatra, Maritime Meteorology Station of Teluk Bayur, and Minangkabau Meteorology Station). This method exhibits the lowest error values and the strongest correlation between predicted and actual data. This is evident from the Nash-Sutcliffe Efficiency (NSE) values, which are 0.188214535, 0.613823746, and 0.545734162 (unsatisfactory-satisfactory), as well as the obtained correlation values of 0.472103386, 0.795586268, and 0.743002591 (moderate-strong). However, this method is unable to perfectly capture outlier values. These outliers arise as a result of unusual conditions, such as natural disasters or climate changes, and atmospheric phenomena like El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD), leading to exceptionally high or low precipitation.
Co-Authors Afghani, Fadhli Aslama