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All Journal GEOGRAPHIA: Jurnal Pendidikan dan Penelitian Geografi
Abdul Aziz Al Badri
Program Studi Meteorologi Sekolah Tinggi Meteorologi Klimatologi dan Geofisika
Earth & Planetary Sciences Education Environmental Science Social Sciences Other

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Optimalisasi Model ARIMA dalam Prakiraan Curah Hujan di Jambi Alya Claudina Anggun Nandarie; Abdul Aziz Al Badri; Yosafat Donni Haryanto
GEOGRAPHIA : Jurnal Pendidikan dan Penelitian Geografi Vol. 4 No. 1 (2023): Juni
Publisher : Jurusan Pendidikan Geografi Universitas Negeri Manado

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53682/gjppg.v4i1.5776

Abstract

Process determine predicted monthly rainfall values for 2022, this study models rainfall forecasts. Observations of monthly rainfall over 30 years (1992–2022) were used to collect the data. The data is then analyzed using the Minitab application's ARIMA model to examine historical trends. For each model utilized, the forecast results are connected with the actual observation data in 2022. The model (1,0,1), (1,0,1) is used to calculate the difference to acquire a result of 54%, which is the best correlation value. The most accurate model for predicting monthly rainfall in Jambi is this one.
Analisis Kondisi Atmosfer pada Kejadian Hujan ES di Kota Palembang 04 November 2023 Abdul Aziz Al Badri; Yahya Darmawan
GEOGRAPHIA : Jurnal Pendidikan dan Penelitian Geografi Vol. 5 No. 1 (2024): Juni
Publisher : Jurusan Pendidikan Geografi Universitas Negeri Manado

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53682/gjppg.v5i1.8469

Abstract

Seasonal transitions in Indonesia are typically accompanied by extreme weather phenomena, such as hail that occurred in the city of Palembang on November 4, 2023. The analysis of atmospheric conditions is intended to understand the dynamics of the atmosphere during the occurrence of the hailstorm phenomenon. The data used in this study include satellite imagery from Himawari-9 channels 8, 11, 13, 15, GSM data, ECMWF modelling data, and SST anomaly data. The research results indicate that anomalies in sea surface temperature and vertical convergence profiles, as well as relative humidity (RH), strengthen the potential for convective activity leading to extreme weather conditions. Based on Himawari-9 satellite imagery, the time series graph shows the lowest peak cloud temperature at around -80°C, with the Atmospheric Stability Index based on the GSM method indicating a labile atmospheric condition. Furthermore, using the RGB 24 Hour Microphysics and CCO methods, Cumulonimbus clouds were observed to begin growing at 07:20 UTC, entering the mature stage at 09:20 UTC, and starting to decay at 10:20 UTC.
Co-Authors Alya Claudina Anggun Nandarie Yahya Darmawan Yosafat Donni Haryanto