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All Journal Jurnal Ilmu Komputer dan Informasi Lontar Komputer: Jurnal Ilmiah Teknologi Informasi ILMU KELAUTAN: Indonesian Journal of Marine Sciences POSITRON Jurnal INKOM Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Jurnal Teknologi dan Sistem Komputer Jurnal Tanah dan Iklim
Arnida Lailatul Latifah
Telkom University
Agriculture, Biological Sciences & Forestry Computer Science & IT Earth & Planetary Sciences Electrical & Electronics Engineering Energy Environmental Science Physics

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Prediksi Luas Kebakaran Hutan dan Lahan pada Tahun 1997-2005 Akibat Faktor Antropogenik Menggunakan Data CMIP5 Lesi Mareta; Arnida Lailatul Latifah; Rahmat Hidayat; Rini Hidayati
Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Vol. 11 No. 2 (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.11.2.324-333

Abstract

Kebakaran hutan dan lahan (Karhutla) merupakan sebuah bencana lokal dan nasional tahunan yang ada di Indonesia. Kebakaran hutan dan lahan secara garis besar dipengaruhi oleh dua faktor, yaitu terjadi karena alami (Natural forcing) dan/atau aktivitas manusia (Anthropogenic forcing). Aktivitas manusia tersebut melepaskan sejumlah besar karbon dioksida (CO2), karbon monoksida (CO), metana (CH4), oksidanitrat, nitrogen dioksida (NOx) dan partikulat yang bertindak sebagai sumber pemanasan rumah kaca yang telah dipantau oleh satelit beberapa tahun terakhir. Penelitian ini mengkaji luas karhutla dalam beberapa dekade terakhir akibat pengaruh faktor antropogenik di Kalimantan menggunakan dua jenis kelompok data yang akan dianalisa yaitu data tanpa dan dengan komponen antropogenik. Analisa dilakukan dengan memanfaatkan data luaran CMIP5. Studi ini menggunakan pendekatan statistik teknik Random Forests (RF) untuk mengevaluasi kontribusi faktor iklim dan antropogenik terhadap luas karhutla di daerah Kalimantan. Kondisi umum luas karhutla berdasarkan data observasi yang diperoleh dari data GFED. Dua luas tertinggi yang terjadi di Kalimantan selama periode 1997 hingga 2005 terjadi pada tahun 1997 dan 2002 Menurut ketiga model pada tahun 1997 dan 2002 terlihat bahwa faktor antropogenik memberikan pengaruh lebih dominan terhadap luas karhutla di Kalimantan. Pada tahun 1997 dan 2002 luas karhutla akibat pengaruh antropogenik bernilai positif (menyebabkan luas karhutla meningkat).
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

Abstract

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 Nurhadiyatna Andi Ihwan Ayu Shabrina Didit Adytia Furqon Hensan Muttaqien Hidayat Pawitan Inna Syafarina Inna Syafarina Intan Nuni Wahyuni Intan Nuni Wahyuni Irza Arnita Nur Lesi Mareta Mareta, Lesi Misnawati Muh. Taufik Nurhadiyatna, Adi Rahmat Hidayat Rahmat Hidayat Rahmat Hidayat Rini Hidayati Semeidi Husrin Syam Budi Iryanto Taufiq Wirahman