Garuda - Garba Rujukan Digital

p-Index From 2020 - 2025

0.983

P-Index

This Author published in this journals

All Journal Agromet Indonesian Journal of Geography Majalah Geografi Indonesia Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Forum Geografi Omni-Akuatika Jurnal Sains & Teknologi Modifikasi Cuaca Jurnal Tanah dan Iklim

Rahmat Hidayat

Departemen Geofisika Dan Meteorologi, Fakultas Fakultas Matematika Dan Ilmu Pengetahuan Alam, Institut Pertanian Bogor

Author-ID : 2481574

Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Earth & Planetary Sciences Education Environmental Science

Published : 11 Documents Claim Missing Document

Claim Missing Document

Articles

1 2

PENGARUH FAKTOR ALAMI DAN ANTROPOGENIK TERHADAP LUAS KEBAKARAN HUTAN DAN LAHAN DI KALIMANTAN Mareta, Lesi; Hidayat, Rahmat; Hidayati, Rini; Latifah, Arnida Lailatul
Jurnal Tanah dan Iklim (Indonesian Soil and Climate Journal) Vol 43, No 2 (2019)
Publisher : Balai Besar Penelitian dan Pengembangan Sumberdaya Lahan Pertanian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21082/jti.v43n2.2019.147-155

Abstrak. Kebakaran hutan dan lahan (karhutla) di Indonesia khususnya di Kalimantan menjadi ancaman bagi pembangunan berkelanjutan karena efeknya secara langsung bagi ekosistem, berkontribusi pada peningkatan emisi karbon dan berdampak pada keanekaragaman hayati. Karhutla dipengaruhi oleh faktor alami dan faktor antropogenik oleh aktivitas manusia. Penelitian ini bertujuan untuk mendapatkan gambaran pengaruh faktor alami dan antropogenik secara terpisah terhadap luas kebakaran hutan dan lahan di Kalimantan. Pengaruh faktor alami dan antropogenik terhadap luas karhutla dianalisis dari data luaran model CMIP5 dengan teknik statistik Random Forests. Penelitian menggunakan data iklim dan data indeks karhutla. Data iklim terdiri dari variabel kelembaban relatif permukaan, suhu udara permukaan, dan curah hujan yang diperoleh dari luaran model MRI-CGCM3 CMIP5. Data indeks karhutla di Kalimantan diperoleh dari data Global Fire Emissions Database (GFED). Hasil analisis pada periode data tahun 1997 sampai dengan 2005 memperlihatkan karhutla terluas di Kalimantan terjadi pada tahun 1997 dan 2002. Variasi musiman historis luas karhutla di Kalimantan menunjukkan peningkatan pada bulan Juni, mencapai puncaknya pada bulan September dan mulai berkurang pada bulan November. Pada bulan Juni hingga Juli, faktor antropogenik bernilai positif yang berarti mengurangi kejadian kebakaran, sedangkan pada bulan Agustus hingga Oktober faktor antropogenik bernilai negatif, menyebabkan lebih banyak peristiwa karhutla.Abstract. Forest and land fires in Indonesia, especially in Kalimantan, are considered as a threat to sustainable development because of their direct effect on ecosystems, their contribution to increasing carbon emissions, and their impact on biodiversity. Forest and land fires are influenced by two main factors, namely climate conditions, and human activity (anthropogenic) factors. The objective of this research was to analyze the influence of natural and anthropogenic factors on the area of forest and land fires in Kalimantan. The anthropogenic effects on the area of burn scars can be analyzed by using the output of the CMIP5 model with statistical techniques, Random Forests. The data used are climate data and index data on forest and land fires in Kalimantan. Climate data consist of the variables: surface relative humidity, surface air temperature, and rainfall which were obtained from the output of the MRI-CGCM3 CMIP5 model. Indices of Forest and land fires in Kalimantan were obtained from Global Fire Emissions Database (GFED). The results of the analysis showed that extensive forest and land fires during the period of 1997 to 2005 in Kalimantan, occurred in 1997 and 2002. Historically extensive seasonal variations of Forest and land fires in Kalimantan increased in June, reaching the peak in September and decreased in November. Between June and July, anthropogenic factors positively influenced (causing less burned area), while from August to October had a negative effect (causing larger) burned areas.

Variabilitas Curah Hujan Indonesia dan Hubungannya dengan ENSO/IOD: Estimasi Menggunakan Data JRA-25/JCDAS Rahmat Hidayat; Kentaro Ando
Agromet Vol. 28 No. 1 (2014)
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Rainfall variability over Indonesia and its relation to El Niño – Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) events were investigated using the Japanese 25-year reanalysis/Japan Meteorological Agency (JMA) Climate Data Assimilation System (JRA-25/ JCDAS). The JRA-25 data consistently depicts seasonal variation of Indonesian rainfall with a wet season that peaks at December-January and a dry season that peaks in July-August when the convection belt moved northward. Composite analysis of rainfall, sea surface temperature and low-level wind anomalies have shown that the impact of ENSO/IOD on rainfall variations in Indonesia is clearly dominant during dry season. Drought conditions typically occur during El Niño years when SST anomalies surrounding Indonesia are cool and walker circulation is weakened, resulting in anomalous surface easterlies across Indonesia. In contrast, in the wet season, the weakening of the relationship between ENSO and Indonesian rainfall is linked to the transition between surface southeasterlies to northwesterlies. At this time persistent surface easterly anomalies across Indonesia superimposed on the climatological mean winds during a warm phase of ENSO event acts to reduce the wind speed resulting reduced the negative DJF rainfall anomalies.

Season Onset Prediction Based on Statistical Model for Malang Regency, East Java Fithriya Y Rohmawati; Urfana Istiqomah; Rahmat Hidayat
Agromet Vol. 36 No. 1 (2022): JUNE 2022
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/j.agromet.36.1.21-30

Prediction of season onset is important for many sectors, particularly on agricultural practices, as its usage for reducing climate risk and planning activities. Current knowledge on season onset prediction mainly focused on large area, which remains research challenge for local level. This research developed model prediction of season onset for Malang Regency, East Java based on global climate data. The research specifically aimed to: (i) determine the onset date of rainy and dry season, (ii) generate equation for onset date prediction using principal component regression (PCR) approach, and (iii) evaluate the model performance. We depend on statistical model based on a combine of domain time and principal component analysis (PCA) for atmospheric variables, namely sea level pressure, outgoing longwave radiation, and zonal wind. We used the Tropical Rainfall Measuring Mission (TRMM) data for model evaluation, especially for determination of onset date. Based on cumulative anomalies rainfall, the onset date for dry season occurred in the early May, whereas for rainy season it was in early November. The results showed that regression models of the principal components had a good skill to predict onset date for both seasons. It has been confirmed by a low error and a high correlation. Visually, the dynamic of onset dates from model was mostly identical to the observation. The predictive model for rainy season had higher performance compared to the model for dry season. This finding was confirmed by insignificant difference resulted from the independent t-test between model and observed onset dates. The best model for dry season was conducted by domain time of February, whereas for rainy season was domain time of August. This research can be used to complement previous studies regarding season onset prediction in Indonesia.

Perubahan Temperature Humidity Index (THI) di Pulau Jawa sejak 1981 hingga 2019 Qurrata A'yun Kartika; Rahmat Hidayat; Rista Hernandi Virgianto
Majalah Geografi Indonesia Vol 35, No 2 (2021): Majalah Geografi Indonesia
Publisher : Fakultas Geografi, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/mgi.63432

Abstrak Pulau Jawa mengalami peningkatan jumlah penduduk dari waktu ke waktu. Peningkatan ini berdampak pada tingginya aktivitas antropogenik yang menghasilkan emisi yang diantaranya dapat menyebabkan perubahan suhu udara. Suhu udara sangat berkaitan dengan thermal stress yang mempengaruhi kenyamanan bahkan kesehatan manusia. Thermal stress dapat diukur dengan Temperature Humidity Index (THI) dengan suhu udara rata-rata permukaan dan Relative Humidity (RH) sebagai variabel bebas. Penelitian ini menganalisis sejauh mana perubahan suhu udara permukaan, RH dan THI terhadap waktu. Kemudian daerah dengan perubahan THI yang paling besar akan dianalisis keterkaitannya jumlah penduduk menggunakan korelasi Pearson. Berdasarkan hasil penelitian diketahui terjadi perubahan suhu udara udara permukaan sebesar -0.27 hingga 1.17⁰C diikuti perubahan RH sebesar -2.21% hingga 0.77% dan terjadi perubahan THI hingga 0,72⁰C sejak 1981 hingga 2019 terutama di pesisir utara bagian barat Pulau Jawa. Selain itu, THI di sekitar DKI Jakarta juga memiliki nilai korelasi simultan yang tinggi dengan jumlah penduduk sebesar 0,81, korelasi lag 1 tahun sebesar 0,69, sementara korelasi lag 2 tahun sebesar 0,67. Temuan ini mengindikasikan peningkatan jumlah penduduk berdampak terhadap peningkatan THI pada DKI Jakarta. Abstract Java has experienced an increase in population from time to time. This increase has an impact on high anthropogenic activity which results in emissions, which can cause changes in air temperature. Air temperature is closely related to thermal stress which affects comfort and even human health. Thermal stress can be measured by the Temperature Humidity Index (THI) with the average surface air temperature and Relative Humidity (RH) as the independent variable. This study analyzes the extent of changes in surface air temperature, RH and THI with time. Then the areas with the greatest THI changes will be analyzed for their correlation using the Pearson correlation. Based on the research results, it is found that there has been a change in surface air temperature of -0.27 to 1.17⁰C followed by changes in RH from -2.21% to 0.77% and there has been a change in THI to 0.72⁰C from 1981 to 2019, especially on the north coast of the western part of Java. In addition, THI around DKI Jakarta also has a high simultaneous correlation value with a population of 0.81, a 1-year lag correlation of 0.69, while a 2-year lag correlation of 0.67. These findings indicate an increase in population has an impact on increasing THI in DKI Jakarta.

PERBAIKAN ESTIMASI CURAH HUJAN BERBASIS DATA SATELIT DENGAN MEMPERHITUNGKAN FAKTOR PERTUMBUHAN AWAN Adi Mulsandi; Mamenun Mamenun; Lutfi Fitriano; Rahmat Hidayat
Jurnal Sains & Teknologi Modifikasi Cuaca Vol. 20 No. 2 (2019): December 2019
Publisher : BPPT

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29122/jstmc.v20i2.3810

Intisari Permasalahan utama dalam mengestimasi curah hujan menggunakan data satelit adalah kegagalan membedakan antara awan cumuliform dengan awan stratiform dimana dapat menyebabkan nilai estimasi hujan under/overestimate. Dalam penelitian ini teknik estimasi curah hujan berbasis satelit yang digunakan adalah modifikasi Convective Stratiform Technique (CSTm). CSTm memiliki kelemahan ketika harus menghitung sistem awan konveksi dengan inti konveksi yang sangat luas karena akan memiliki nilai slope parameter kecil, sehingga menghasilkan estimasi curah hujan yang underestimate. Dengan melibatkan perhitungan faktor pertumbuhan awan di algoritma CSTm permasalahan tersebut dapat diatasi. Penelitian ini menerapkan algoritma CSTm dan faktor pertumbuhan awan (CSTm+Growth Factor) untuk mengestimasi kejadian hujan lebat yang menyebabkan banjir di Jakarta pada tanggal 24 Januari 2016 yang digunakan juga sebagai studi kasus di proyek pengembangan model NWP di BMKG. Hasil penelitian menunjukan bahwa perlibatan faktor pertumbuhan awan sangat efektif memperbaiki kelemahan teknik CSTm, diperlihatkan dengan peningkatan nilai korelasi dari 0.6 menjadi 0.8 untuk wilayah Kemayoran dan -0.1 menjadi 0.83 untuk wilayah Cengkareng. Secara umum gabungan teknik CSTm dan faktor pertumbuhan awan dapat memperbaiki estimasi nilai intensitas dan fase hujan.Â AbstractÂ The main problem in estimating rainfall using satellite data is a failure to distinguish between cumuliform and stratiform clouds, which can cause under/overestimate of rains. In this research, the Modified Convective Stratiform Technique (CSTm) has been used to estimate rainfall based on satellite data. The weakness of the CSTm technique is defined when calculating the convective cloud system within a widely convective point. Cloud convective will have a low value of parameter slope and produce an underestimate of rainfall. This issue can be resolved by calculating the cloud growth factor on CSTm. CSTm algorithm and cloud growth factor (CSTm+Growth Factor) has been applied to this research to estimate heavy rainfall for floods event in Jakarta area on January 24th, 2016. The result showed that the cloud growth factor is very effective in improving the weakness of rainfall estimation using the CSTm technique. Correlation between estimation and observation rainfall has increased from 0,6 to 0,8 on Kemayoran and from -0,1 to 0,83 on Cengkareng. The coupled method of CSTm and cloud growth factor significantly improve in estimating phase and intensity of rainfall.

Identification of Upwelling Area of the Western Territorial Waters of Indonesia From 2000 To 2017 Eko Supriyadi; Rahmat Hidayat
Indonesian Journal of Geography Vol 52, No 1 (2020): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

The Western Waters of Indonesian (WWI) present a diverse interaction of ocean-atmosphere dynamics. One of them represents the event of Indian Ocean Dipole (IOD), El Niño–Southern Oscillation (ENSO), and upwelling. The objective of this study is to determine the dynamics of chlorophyll-a concentration (Chl–a), especially during IOD and ENSO. Also, this study is aimed to examine the temporal and spatial distribution of the upwelling area from 2000 to 2017. The data utilized consisted of Chl–a, wind stress, Sea Level Anomaly (SLA), and Sea Surface Temperature (SST). The technique used to determine the upwelling area was by examining the maximum conditions of Chl–a, the low temperature of SST, and SLA. The results showed the sea surface temperature had a relationship with the concentration of Chl–a. It was obtained if the Directional Movement Index (DMI) and N3.4 (Niño 3.4 Index) moved stably (not too fluctuation) resulting in high concentrations of Chl–a. High standard deviations of SST are recognized around the Sunda Strait (June – October). When the standard deviation of SST is high, there is also a tendency for high Chl–a concentrations, while the results of empirical calculations show that large areas of upwelling occurred in January and September respectively at 12,447.72 km2 and 8,146.20 km2. Based on the results of the analysis, it can be concluded that the upwelling does not only occur at the coastal area of Western Sumatra (coastal upwelling), but it also occurs in the eastern territorial waters of the Indian Ocean. In addition, the upwelling area has the same pattern as the Chl–a concentration in January - October.

Using 3D-Var Data Assimilation for Improving the Accuracy of Initial Condition of Weather Research and Forecasting (WRF) Model in Java Region (Case Study : 23 January 2015) Novvria Sagita; Rini Hidayati; Rahmat Hidayat; Indra Gustari; Fatkhuroyan Fatkhuroyan
Forum Geografi Vol 30, No 2 (2016): December 2016
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v30i2.2512

Weather Research and Forecasting (WRF) is a numerical weather prediction model developed by various parties due to its open source, but the WRF has the disadvantage of low accuracy in weather prediction. One reason of low accuracy of model is inaccuracy initial condition model to the actual atmospheric conditions. Techniques to improve the initial condition model is the observation data assimilation. In this study, we used three-dimensional variational (3D-Var) to perform data assimilation of some observation data. Observational data used in data assimilation are observation data from basic stations, non-basic stations, radiosonde data, and The Binary Universal Form for the Representation of meteorological data (BUFR) data from the National Centers for Environmental Prediction (NCEP) , and aggregate observation data from all stations. The aim of this study compares the effect of data assimilation with different data observation on January 23, 2015 at 00.00 UTC for Java island region. The results showed that changes root mean square error (RMSE) of surface temperature from 2° C to 1.7° C - 2.4° C, dew point from 2.1o C to 1.9o C - 1.4o C, relative humidity from 16.1% to 3.5% - 14.5% after the data assimilation.

Kerentanan Penghidupan Masyarakat Pesisir Perkotaan Terhadap Variabilitas Iklim (Studi Kasus di Kota Kupang) Liky Ledoh; Arif Satria; Rahmat Hidayat
Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Vol. 9 No. 3 (2019): Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan
Publisher : Graduate School Bogor Agricultural University (SPs IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jpsl.9.3.758-770

Adaptation to climate change cannot be separated from the climatic conditions and vulnerability of local communities. This study aims to determine the vulnerability of household livelihoods in urban coastal areas to climate variability. This research was conducted in coastal city of Kupang. Community livelihood vulnerability analysis using vulnerability index (LVI and LVI-IPCC). In addition, an analysis of climate variability of rainfall and average temperature from 1988-2017 was also carried out. The results of the study show that climate variability is seen in decreases in rainfall and and increase in surface temperature in the past 30 years. The LVI and LVI-IPCC scores also show the vulnerability of livelihoods on a medium scale in three sample villages. Climate variability in urban coasts can have an impact on coastal communities on the components of livelihood strategies, food, homes and land and water which are generally influenced by climatic factors. Non-vulnerable components such as health support the vulnerable components as part of the adaptation process

Identifikasi perubahan suhu udara dan curah hujan di Bogor Rahmat Hidayat; Alfi Wardah Farihah
Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Vol. 10 No. 4 (2020): Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (JPSL)
Publisher : Graduate School Bogor Agricultural University (SPs IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jpsl.10.4.616-626

Climate datasets were analyzed to identify the changing climatic parameters and extreme events in Bogor, West Java. This study aims to analyze the characteristic of observational datasets in Baranangsiang and Dramaga, namely, air temperature and rainfall, and to indentify the changing structure of those climate parameters. The analysis has been conducted using RClimdex to understand the long-term changing air temperature and rainfall based on 10 indices for air temperature and 8 indices for rainfall. Results show that the rainfall in Baranangsiang has the daily mean of 10 mm/day and in Dramaga of 8 mm/day. The daily mean of air temperature in Baranangsiang and Dramaga is 27˚C and 25.5˚C, respectively. Generally, the declined slopes of the temperature indices in Barangsiang, namely, TN90p, TNx, TX10p, TNn, TXn, TR20, and SU25, indicate cooler temperature. In Dramaga, the increased temperature indices, namely, TN90p, TX90p, TXx, SU25, and TXn, indicate the warmer temperature. The rainfall indices generally decline, except for CDD, which indicate the increased consecutive dry days in Baranangsiang.

Pengaruh koreksi bias dan metode ensemble pada data curah hujan dari empat model luaran Regional Climate Model (RCM) CORDEX-SEA di Sumatera Irza Arnita Nur; Rahmat Hidayat; Arnida Lailatul Latifah; Misnawati
Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Vol. 11 No. 1 (2021): Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (JPSL)
Publisher : Graduate School Bogor Agricultural University (SPs IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jpsl.11.1.49-56

Drought is a natural disaster that occurs slowly and lasts longer until the wet season occurred. Drought occurred in expected time, so that preparations and preparedness can be made in dealing with drought disasters. Therefore, we need an overview of future drought events (or projections).In this study, Standardized Precipitation Index (SPI) was used as drought index. The occurrence of drought is closely related to weather factors and occurs repeatedly. Time-series weather data is needed to know the time-series weather conditions. Problems with data that often occur can be overcome by using numerical climate modeling which is currently widely used. Regional Climate Model (RCM) is a climate model that can be used to build long-term climate data, both time-series and projection data. The results showed RCM model data required bias correction in order to reduce bias in the CORDEX RCM model data. RCM rainfall models before correction were still biased. Thus, bias correction is needed to reduce bias in models data. Time series obtained from SPI baseline data for 2000-2005 in Lampung and West Sumatra provinces showed SPI value which smaller than the projection SPI value in 2021-2030. While SPI time series with RCP 4.5 and 8.5 scenarios showed different results. SPI with RCP 8.5 scenario have more negative value so that drought occurred more often than RCP 4.5. The negative SPI index that often occured in RCP 8.5 scenario appeared to be in RCM IPSL and MPI models year 2025-2030.

Co-Authors Adi Mulsandi Ahmad Bey Alfi Wardah Farihah Arif Satria Arnida Lailatul Latifah Danang Eko Nuryanto Edvin Aldrian Eko Supriyadi Fatkhuroyan Fatkhuroyan Fithriya Yulisiasih Rohmawati Herlina Ika Ratnawati Hidayat Pawitan Indra Gustari Irza Arnita Nur Kartika, Qurrata A'yun Kentaro Ando Liky Ledoh Lutfi Fitriano Mamenun Mamenun Mareta, Lesi Misnawati Novvria Sagita Rini Hidayati Rista Hernandi Virgianto Tania June Urfana Istiqomah

Title

Found 11 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 11 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 11 Documents
Search