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Copula in Wildfire Analysis: A Systematic Literature Review Najib, Mohamad Khoirun; Nurdiati, Sri; Sopaheluwakan, Ardhasena
InPrime: Indonesian Journal of Pure and Applied Mathematics Vol 3, No 2 (2021)
Publisher : Department of Mathematics, Faculty of Sciences and Technology, UIN Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/inprime.v3i2.22131

AbstractCopula model is a method that can be implemented in various study fields, including analyzing wildfires. The copula distribution function gives a simple way to define joint distribution between two or more random variables. This study aims to review the application of copula in the analysis of wildfires using a Systematic Literature Review (SLR) and provide insight into research opportunities related to the application in Indonesia. The results show there are very few articles using the copula model in the analysis of wildfires. However, the increasing number of article citations each year shows the importance of such article research and has contributed to wildfire analysis development. In that article, 50% of studies applied the copula model to direct wildfire analysis (using fire data) in Canada, Portugal, and the US. Meanwhile, the other 50% use the copula model for indirect wildfire analysis (not using fire data) in Canada and the European region. The outcome of the presented review will provide the latest research positions and future research opportunities on the application of copula in the analysis of wildfires in Indonesia.Keywords: copula; wildfire; systematic literature review. AbstrakModel copula merupakan metode yang dapat diimplementasikan pada berbagai bidang penelitian, salah satunya pada analisis kebakaran hutan. Fungsi sebaran copula memberikan cara yang mudah untuk mendefinisikan sebaran peluang bersama antara dua peubah acak atau lebih. Tujuan penelitian ini mengulas penerapan model copula tersebut pada analisis kebakaran hutan dalam studi literatur menggunakan Systematic Literature Review (SLR) serta memberikan peluang riset ke depan terkait implementasinya pada analisis kebakaran hutan di Indonesia. Hasil penelitian menunjukkan bahwa model copula pada analisis kebakaran hutan masih sangat sedikit. Namun, peningkatan jumlah sitasi artikel tiap tahun menunjukkan pentingnya penelitian tersebut dan memiliki kontribusi pada perkembangan analisis kebakaran hutan. Pada artikel tersebut, sebanyak 50% penelitian menerapkan model copula pada analisis kebakaran secara langsung (menggunakan data kebakaran) di Kanada, Portugal, dan Amerika. Sementara, sebanyak 50% lainnya menerapkan model copula pada analisis kebakaran secara tak langsung (tidak menggunakan data kebakaran), yaitu di Kanada dan kawasan Eropa. Hasil tinjauan memberikan posisi riset terkini serta usulan riset ke depan mengenai penerapan model copula untuk analisis kebakaran hutan dan lahan di Indonesia.Kata kunci: copula; kebakaran hutan; studi literatur sistematik.

Modeling of Heavy Rainfall Triggering Landslide Using WRF Model Nuryanto, Danang Eko; Fajariana, Yuaning; Pradana, Radyan Putra; Anggraeni, Rian; Badri, Imelda Ummiyatul; Sopaheluwakan, Ardhasena
Agromet Vol. 34 No. 1 (2020): JUNE 2020
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

This study revealed the behavior of heavy rainfall before landslide event based on the Weather Research Forecasting (WRF) model. Simulations were carried out to capture the heavy rainfall patterns on 27 November 2018 in Kulonprogo, Yogyakarta. The modeling was performed with three different planetary boundary layer schemes, namely: Yonsei University (YSU), Sin-Hong (SH) and Bougeault and Lacarrere (BL). Our results indicated that the variation of rainfall distribution were small among schemes. The finding revealed that the model was able to capture the radar’s rainfall pattern. Based on statistical metric, WRF-YSU scheme was the best outperforming to predict a temporal pattern. Further, the study showed a pattern of rainfall development coming from the southern coastal of Java before 13:00 LT (Local Time=WIB=UTC+7) and continued to inland after 13:00 LT. During these periods, the new clouds were developed. Based on our analysis, the cloud formation that generated rainfall started at 10:00 LT, and hit a peak at 13:00 LT. A starting time of cloud generating rainfall may be an early indicator of landslide.

Statistical bias correction on the climate model for el nino index prediction Nurdiati, Sri; Sopaheluwakan, Ardhasena; Pratama, Yoga Abdi; Najib, Mohamad Khoirun
Al-Jabar: Jurnal Pendidikan Matematika Vol 12 No 2 (2021): Al-Jabar: Jurnal Pendidikan Matematika
Publisher : Universitas Islam Raden Intan Lampung, INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ajpm.v12i2.8884

El Nino can harm many sectors in Indonesia by reducing precipitation levels in some areas. The occurrence of El Nino can be estimated by observing the sea surface temperature in Nino 3.4 region. Therefore, an accurate model on sea surface temperature prediction in Nino 3.4 region is needed to optimize the estimation of the occurrence of El Nino, such as ECMWF. However, the prediction model released by ECMWF still consists of some systematic errors or biases. This research aims to correct these biases using statistical bias correction techniques and evaluate the prediction model before and after correction. The statistical bias correction uses linear scaling, variance scaling, and distribution mapping techniques. The results show that statistical bias correction can reduce the prediction model bias. Also, the distribution mapping and variance scaling are more accurate than the linear scaling technique. Distribution mapping has better RMSE in December-March, and variance scaling has better RMSE in April-June also in October and November. However, in July-September, prediction from ECMWF has better RMSE. The application of statistical bias correction techniques has the highest refinement in January-March at the first lead time and in April at the fifth until the seventh lead time.

PEMODELAN STATISTIK DAN SIMPLE RADIATIVE MODEL UNTUK MENDUGA RADIASI MATAHARI GLOBAL HARIAN Ilahi, Asep Firman; Sopaheluwakan, Ardhasena
Megasains Vol 8 No 1 (2017): Megasains Vol. 8 No. 1 Tahun 2017
Publisher : Stasiun Pemantau Atmosfer Global Bukit Kototabang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46824/megasains.v8i1.186

Artikel ini mengevaluasi akurasi dan penerapan tujuh radiasi matahari global estimasi yang menggunakan suhu lingkungan harian, curah hujan total dan kelembaban relatif di kawasan tropis benua maritim Indonesia. Dua model yang dievaluasi ini adalah model baru model yang diusulkan (PM) untuk memperkirakan tenaga surya radiasi pada permukaan horizontal. Pertama model PM1 menggunakan suhu-presipitasi sebagai input (berbasis TP) sedangkan PM2 kedua Model yang digunakan adalah suhu-presipitasi-relatif kombinasi kelembaban sebagai input (berbasis TPRH). Semua model dievaluasi berdasarkan kesalahan statistik mis. Fraksi Prediksi dalam satu atau dua faktor (FAC2), Mean Bias (MB), Mean Kesalahan Kotor (MGE), Bias Rata-rata yang Dinormalisasi (NMB), Rata-rata Kesalahan Kotor yang Dinormalisasi (NMGE), Kesalahan Root Mean Square (RMSE), Koefisien determinasi (r) dan Koefisien Efisiensi (COE). Hasil penelitian menunjukkan bahwa berbasis TPRH model memiliki akurasi yang lebih baik dibandingkan berbasis T atau berbasis TP. Model PM2 menunjukkan performa terbaik di antara semua model saat Quej et.al model 2016 memiliki akurasi yang baik namun kurang presisi. Ciri-ciri iklim tropis dimana kelembaban tinggi sangat mempengaruhi radiasi matahari yang masuk ke permukaan sementara atau spasial.

Developing Surface Rainfall Data Based on Blending of Satellite-Based Products and Rain Gauge Observations in the Ngawi Region, East Java Utomo, Joko Budi; Yuli Handoko, Eko; Aldila Syariz, Muhammad; Sopaheluwakan, Ardhasena
Jurnal Ilmu Fisika Vol 17 No 2 (2025): September 2025
Publisher : Jurusan Fisika FMIPA Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jif.17.2.110-124.2025

Rainfall estimation can be performed using various methods, including direct satellite observations (RR-Satellite). However, these estimates show discrepancies when compared to actual observations in-situ rain gauges (RR-Obs). To address this challenge, one potential solution is integrating RR-Satellite with RR-Obs. The Kriging with External Drift (KED) interpolation method is a blending technique that incorporates RR-Satellite as external drift. This study utilized four satellite dataset, namely CHIRP, CMORPH, GSMAP_V8, and IMERG as auxiliary information to generate monthly rainfall estimates (RR-Blended) at 26 rain gauges in Ngawi, East Java, for the period 2001 - 2023. The performance of each satellite dataset was evaluated using Leave-One-Out Cross Validation (LOOCV). The results indicated that RR-Blended using CHIRP (bCHIRP) demonstrated the best accuracy at the climatological scale, with KGE > 0.3 and TSS > 0.65, outperforming other satellite dataset. At the monthly scale, bCHIRP, bCMORPH, and bIMERG showed better performance in different months throughout the year. In terms of spatial accuracy, bCMORPH achieved the highest performance. Our findings suggest that each satellite offers unique advantages based on the time and location of observation. Therefore, we recommend using a weighted combination of RR-Blended from four satellites as the most effective approach for obtaining the best rainfall estimates.

VALIDASI SILANG REGRESI RIDGE DAN STEPWISE UNTUK PERSAMAAN TERGENERALISASI ANTARA DEBIT BENDUNGAN SUTAMI DAN CURAH HUJAN WILAYAH Luthfi, Ahmad; Handoko, Eko Yuli; Muhammad, Aldila Syariz; Sopaheluwakan, Ardhasena; Kurniawan, Andang
Jurnal Geosaintek Vol. 11 No. 2 (2025)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25023659.v11i2.5163

Informasi debit masuk bendungan sangat krusial untuk pengelolaan sumber daya air di Bendungan Sutami, Daerah Aliran Sungai (DAS) Brantas Hulu, Jawa Timur. Tantangan utama dalam penelitian ini adalah konversi data curah hujan dasarian menjadi informasi debit yang mampu menghadapi kendala terkait konsistensi sehingga memerlukan pendekatan yang lebih robust melalui validasi silang. Penelitian ini mengevaluasi persamaan regresi ridge dan stepwise dengan pendekatan jeda untuk menyusun persamaan curah hujan-debit menggunakan data curah hujan wilayah menggunakan enam raster untuk periode Januari I 2021–Desember III 2023 (108 dasarian). Pemilihan jeda dilakukan melalui analisis korelasi, dengan korelasi negatif sebagai batas penentuan. Regresi stepwise dioptimalkan secara bertahap hingga jeda maksimum, sedangkan regresi ridge diuji dengan rentang lambda 0–50. Persamaan yang dihasilkan divalidasi menggunakan metode validasi silang dengan rasio pembagian data 50:50. Hasil menunjukkan bahwa metode interpolasi Inverse Distance Weighting (IDW) menghasilkan persamaan terbaik, dengan regresi stepwise optimal pada lima variabel prediktor dan regresi ridge pada lambda 0,40. Nilai Mean Absolute Error (MAE) dan koefisien korelasi menunjukkan bahwa persamaan tergeneralisasi dapat menghasilkan galat rendah. Penelitian ini merekomendasikan penggunaan informasi debit permukaan yang dikonversi dari data curah hujan sebagai pengganti parameter sifat hujan dalam perencanaan operasional bendungan, dengan evaluasi bulanan untuk memastikan akurasi model. Kolaborasi antarinstansi disarankan untuk mendukung analisis lanjutan. Hasil penelitian menunjukkan bahwa informasi debit yang dihasilkan mampu mendukung pengelolaan operasional Bendungan Sutami dengan tingkat akurasi yang memadai untuk aplikasi praktis.

Assessing the Influence of Climate Services and Climate Change Adaptation Strategies on Smallholder Agriculture: A Systematic Literature Review Marjuki, Marjuki; Koesmaryono, Yonny; Santikayasa, I Putu; Sopaheluwakan, Ardhasena
Agromet Vol. 39 No. 2 (2025): DECEMBER 2025
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/j.agromet.39.2.75-85

Climate services and climate change adaptation practices are increasingly recognized as essential for supporting smallholder farmers. Despite numerous studies on climate impacts and adaptation strategies, limited systematic evidence exists on how climate services and adaptation interventions influence farming practices across regions. This study addresses the gap through a systematic literature review of Scopus-indexed publications over the past decade. Using the PRISMA approach, 1981 articles were screened, with 31 meeting the eligibility criteria. Of these, 23 focused on adaptation interventions and 8 on climate services. Geographically, 30 studies were concentrated in tropical regions Africa (n =16) and in Asia (n=14), while one study was outside the tropics. Findings show that climate information strongly supports the adoption of adaptation strategies (>60%), especially in technological interventions such as Climate-Smart Agriculture, ecosystem management, irrigation, and climate risk reduction. In terms of service delivery, basic climate service provision demonstrated greater effectiveness (80%) compared to advisory-based agricultural services (40%). Socio-demographic factors, particularly education and age, consistently influenced farmers’ decision-making in adopting both climate services and adaptation practices. Overall, this review highlights the need for more integrated approaches that explicitly connect climate services with adaptation interventions. Strengthening these linkages is especially critical in tropical regions, where smallholder farmers remain highly vulnerable to climate variability and long-term climate change risks.

Probabilistic Prediction Model Using Bayesian Inference in Climate Field: A Systematic Literature Ardiyani, Evi; Nurdiati, Sri; Sopaheluwakan, Ardhasena; Najib, Mohamad Khoirun; Rohimahastuti, Fadillah
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 7, No 3 (2023): July
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v7i3.13651

Wildfires occur repeatedly every year and have a negative impact on natural ecosystems. Anticipation of wildfires is very necessary, therefore a prediction model is needed that can produce predictions with a good level of accuracy. One approach to develop probabilistic prediction models is Bayesian inference. The purpose of this research is to review the methods that can be used in developing probabilistic prediction models using the Bayesian approach. The methodology used is Systematic Literature Review (SLR) which can be used to provide a comprehensive review of Bayesian inference research in developing probabilistic prediction models. The research strategy used was the Boolean Technique applied to database sources including Scopus, IEEE Xplore, and ArXiv. The articles used have novelty and ease of explanation of Bayesian methods, especially predictions in the field of climate so that articles are selected based on inclusion and exclusion criteria. The results show that probabilistic models can provide more accurate results than deterministic models. The Bayesian Model Averaging (BMA) method is a widely used method because it is easy to implement and develop so that the prediction results can be more accurate. The development of probabilistic prediction models with a Bayesian approach has great potential to grow as seen from the development of the number of research publications over the past 5 years. The research position of probabilistic prediction models with Bayesian approaches in the field of climate is dominated by the research community in China with the main problems related to hydrology.TRANSLATE with x EnglishArabicHebrewPolishBulgarianHindiPortugueseCatalanHmong DawRomanianChinese SimplifiedHungarianRussianChinese TraditionalIndonesianSlovakCzechItalianSlovenianDanishJapaneseSpanishDutchKlingonSwedishEnglishKoreanThaiEstonianLatvianTurkishFinnishLithuanianUkrainianFrenchMalayUrduGermanMalteseVietnameseGreekNorwegianWelshHaitian CreolePersian // TRANSLATE with COPY THE URL BELOW Back EMBED THE SNIPPET BELOW IN YOUR SITE Enable collaborative features and customize widget: Bing Webmaster PortalBack//

VARIABILITAS INTERANNUAL HUJAN MONSUN INDONESIA: REVIEW ARTIKEL TENTANG PENGARUH GAYA EKSTERNALNYA Mulsandi, Adi; Koesmaryono, Yonny; Hidayat, Rahmat; Faqih, Akhmad; Sopaheluwakan, Ardhasena
Jurnal Meteorologi dan Geofisika Vol. 24 No. 2 (2023)
Publisher : Pusat Penelitian dan Pengembangan BMKG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31172/jmg.v24i2.1049

The IMR variability is notorious for its hydrometeorological disasters. This paper examines recent studies on IMR and the main factors controlling its variability. The focus of this study is to investigate the impact of the atmosphere-ocean interaction that acts as the external forcing of IMR in the tropical Indian and Pacific Oceans. Specifically, the study will examine the influence of two climate phenomena, namely the El Nino Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) and their interdecadal changes associated Pacific Decadal Oscillation (PDO), on the IMR. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach. Furthermore, data sets (such as rainfall, wind field, and SST) spanning 1990-2020 were used to verify the key findings. In general, this study concludes that the majority of the authors coincided with the following conclusion: ENSO and IOD events impact IMR by changing its amplitude, duration, intensity, and frequency of mean and extreme rainfall. Additionally, it has been shown that their impacts on IMR are most substantial during the dry seasons, specifically in June, July, and August (JJA), and not as strong as during the wet seasons, specifically in December, January, and February (DJF). Spatially, the effects of ENSO and IOD on IMR variability are clearly found more eastward and westward of the region, respectively. The expansions towards the east and west directions were facilitated by the displacement of the ascending and descending of Walker circulation patterns in the Indonesian region, respectively. Given the interannual fluctuations in IMR, caused mainly by ocean-atmosphere interactions, the knowledge gap of atmospheric factors like the Quasi-Biennial Oscillation (QBO) must be investigated in the future, as suggested by previous research and our preliminary study.

Copula in Wildfire Analysis: A Systematic Literature Review Najib, Mohamad Khoirun; Nurdiati, Sri; Sopaheluwakan, Ardhasena
InPrime: Indonesian Journal of Pure and Applied Mathematics Vol. 3 No. 2 (2021)
Publisher : Department of Mathematics, Faculty of Sciences and Technology, UIN Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/inprime.v3i2.22131

AbstractCopula model is a method that can be implemented in various study fields, including analyzing wildfires. The copula distribution function gives a simple way to define joint distribution between two or more random variables. This study aims to review the application of copula in the analysis of wildfires using a Systematic Literature Review (SLR) and provide insight into research opportunities related to the application in Indonesia. The results show there are very few articles using the copula model in the analysis of wildfires. However, the increasing number of article citations each year shows the importance of such article research and has contributed to wildfire analysis development. In that article, 50% of studies applied the copula model to direct wildfire analysis (using fire data) in Canada, Portugal, and the US. Meanwhile, the other 50% use the copula model for indirect wildfire analysis (not using fire data) in Canada and the European region. The outcome of the presented review will provide the latest research positions and future research opportunities on the application of copula in the analysis of wildfires in Indonesia.Keywords: copula; wildfire; systematic literature review. AbstrakModel copula merupakan metode yang dapat diimplementasikan pada berbagai bidang penelitian, salah satunya pada analisis kebakaran hutan. Fungsi sebaran copula memberikan cara yang mudah untuk mendefinisikan sebaran peluang bersama antara dua peubah acak atau lebih. Tujuan penelitian ini mengulas penerapan model copula tersebut pada analisis kebakaran hutan dalam studi literatur menggunakan Systematic Literature Review (SLR) serta memberikan peluang riset ke depan terkait implementasinya pada analisis kebakaran hutan di Indonesia. Hasil penelitian menunjukkan bahwa model copula pada analisis kebakaran hutan masih sangat sedikit. Namun, peningkatan jumlah sitasi artikel tiap tahun menunjukkan pentingnya penelitian tersebut dan memiliki kontribusi pada perkembangan analisis kebakaran hutan. Pada artikel tersebut, sebanyak 50% penelitian menerapkan model copula pada analisis kebakaran secara langsung (menggunakan data kebakaran) di Kanada, Portugal, dan Amerika. Sementara, sebanyak 50% lainnya menerapkan model copula pada analisis kebakaran secara tak langsung (tidak menggunakan data kebakaran), yaitu di Kanada dan kawasan Eropa. Hasil tinjauan memberikan posisi riset terkini serta usulan riset ke depan mengenai penerapan model copula untuk analisis kebakaran hutan dan lahan di Indonesia.Kata kunci: copula; kebakaran hutan; studi literatur sistematik.

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