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All Journal Techno.Com: Jurnal Teknologi Informasi Al-Jabar : Jurnal Pendidikan Matematika Jurnal Matematika: MANTIK Desimal: Jurnal Matematika BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Teorema: Teori dan Riset Matematika Jambura Journal of Mathematics Jambura Geoscience Review Jurnal Matematika UNAND InPrime: Indonesian Journal Of Pure And Applied Mathematics Jambura Journal of Biomathematics (JJBM) Jurnal Pendidikan Progresif Milang Journal of Mathematics and Its Applications Jurnal Matematika Integratif
Najib, Mohamad Khoirun
Department Of Mathematics, Faculty Of Science And Mathematics, IPB University, Jl. Meranti, Kampus IPB Dramaga, Bogor 16680
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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Journal : Jambura Geoscience Review

 1 
Heterogeneous Correlation Map Between Estimated ENSO And IOD From ERA5 And Hotspot In Indonesia Sri Nurdiati; Fahren Bukhari; Muhammad Tito Julianto; Mohamad Khoirun Najib; Nuzhatun Nazria
Jambura Geoscience Review Vol 3, No 2 (2021): Jambura Geoscience Review (JGEOSREV)
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34312/jgeosrev.v3i2.10443

Abstract

El Nino-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) can reduce the amount of rainfall in Indonesia. The previous study found that ENSO and IOD derived from the OISST dataset have an association with hotspots in Indonesia, especially in southern Sumatra dan Kalimantan. But the correlation results are still too small, and the correlation strength between regions has not been analyzed. Therefore, this study quantifies the association of the estimated ENSO and IOD derived from the ERA5 dataset on hotspots in Indonesia based on a Heterogeneous Correlation Map (HCM) and analyzes the correlation strength between regions in Indonesia. We use a singular value decomposition method to quantify this HCM. Besides OISST, ERA5 is an estimation data often used for weather forecast analysis. Therefore, this study quantifies the association of the estimated ENSO and IOD derived from the ERA5 dataset on hotspots in Indonesia based on a Heterogeneous Correlation Map (HCM) and analyzes the correlation strength between regions in Indonesia. Based on variance explained and correlation strength, the hotspot in Indonesia is more sensitive to ENSO and IOD derived from ERA5 than OISST. Consequently, the ERA5 data more useful to statistical analysis that requiring a substantial correlation.
Koreksi Bias Statistik Pada Data Prediksi Suhu Permukaan Air Laut Di Wilayah Indian Ocean Dipole Barat Dan Timur Mohamad Khoirun Najib; Sri Nurdiati
Jambura Geoscience Review Vol 3, No 1 (2021): Jambura Geoscience Review (JGEOSREV)
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34312/jgeosrev.v3i1.8259

Abstract

The IOD can be measured using the Dipole Mode Index (DMI) which is calculated based on the sea surface temperature in the Indian Ocean. Therefore, DMI can be predicted using sea surface temperature forecasting data, such as data provided by the European Center for Medium-Range Weather Forecasts (ECMWF). However, the data still has a bias as compared to the actual data, so to get a more accurate prediction, corrected data is needed. Therefore, the aim of this study is to predict DMI based on sea surface temperature forecasting data that has been corrected for bias using the quantile mapping method, a method that connects the distribution of forecasting and actual data. The results showed that the DMI prediction using corrected data was more accurate than the DMI prediction using ECMWF data. DMI predictions using corrected data have high accuracy to predict IOD events in October-April.
Co-Authors Ardhasena Sopaheluwakan Ardhasena Sopaheluwakan Ardhasena Sopaheluwakan Elis Khatizah Ester Antika Evi Ardiyani Fadillah Rohimahastuti Fahren Bukhari Fahren Bukhari Fahren Bukhari Faiqul Fikri Fitra Nuvus Salsabila Kasiyah Junus Kautsar Hilmi Linda Leni Fatmawati Mochamad Tito Julianto Mochamad Tito Julianto Muhammad Adam Tripranoto Muhammad Reza Ardhana Muhammad Tito Julianto Muhammad Zidane Bayu Nandika Safiqri NGAKAN KOMANG KUTHA ARDHANA Nuzhatun Nazria Refi Revina Ruben Harry Valentdio Salsabilla Rahmah Sri Nurdiati Sri Nurdiati Sri Nurdiati Sri Nurdiati Sri Nurdiati SYAHID AHMAD MUKRIM Trianty Putri Blante Yoga Abdi Pratama