Judul: Estimation of Forest, Plantation, and Land Fires Severity Using Remote Sensing in Dumai, Riau
Abstrak: Kebakaran hutan, kebun, dan lahan merupakan peristiwa terbakarnya hutan dan/atau lahan yang menimbulkan kerugian diberbagai sektor seperti bahaya bencana ekologi, ekonomi, sosial budaya, dan politik. Karhutbunla terjadi akibat dua faktor yaitu faktor alami dan aktivitas manusia. Proses alami terjadinya karhutbunla disebabkan oleh aktivitas pembakaran yang tidak sengaja dan tidak terkendali seperti letusan gunung berapi, sambaran petir pada pohon, serta faktor iklim dan cuaca lainnya. Kota Dumai merupakan salah satu areal terbakar terluas pada tahun 2023. Kota Dumai memiliki lahan gambut seluas 163,141 ha (78%) yang mudah terbakar akibat adanya bahan organik pada tanah. Penelitian ini mengestimasi tingkat keparahan kebakaran hutan, kebun, dan lahan di Kota Dumai pada 2023 menggunakan penginderaan jauh. Penelitian ini menggunakan metode ekstraksi indeks Normalized Burn Ratio yang memetakan area terbakar dan tingkat keparahannya. Hasil menunjukkan area terbesar terjadinya karhutbunla yaitu pada tingkat keparahan “rendah” dengan luas 3.909,67 ha (1,72%). Akurasi menunjukkan tingkat baik (86,67%) untuk identifikasi area terbakar dan tingkat cukup (69%) untuk identifikasi tingkat keparahan kebakaran., Forest, plantation, and land fires are the burning land area that cause losses in sectors such as ecological, economic, social culture, and political dangers and catastrophes. Forest, plantation, and land fires come as a result of two factors: natural factors and human activities. The natural process of the burning is caused by involuntary and uncontrolled burning activities such as volcanic eruptions, lightning strikes in trees, and other climate and weather factors. Dumai city was one of the largest cities with the burning area in 2023. Dumai city had a peat land area of 163,141 ha (78%) that has a tendenct to be flammable because of the accumulation of organic matter in the soil. This study will estimate the severity of forest, plantation, and land fires of Dumai city in 2023 by using remote sensing technology. This research method used is the normalized burn ratio that maps the burn area with its severity. The analysis of the extraction index shows the largest burn areas of forest, plantation, and land area on “low severity” class with an area of 3.909,67 ha (1,72%). Accuracy testing results in a level of good accuracy (86,67%) on burnt area identification and edaquate accuracy (69%) on the burnt severity identification.
Keyword: area terbakar, kebakaran hutan dan lahan, penginderaan jauh

Judul: Estimating the Severity of Peat Fires in Siak Regency, Riau Province
Abstrak: Kebakaran yang terjadi pada lahan gambut memiliki dampak yang sangat buruk bagi kesehatan manusia dan bagi lingkungan. Dampak yang ditimbulkan dari kebakaran tersebut perlu dianalisis lebih lanjut. Salah satu pendekatan dalam penilaian dampak kebakaran adalah pendekatan tingkat keparahan kebakaran (fire severity) yang menilai dampak kebakaran terhadap vegetasi dan sifat-sifat tanah. Perkembangan teknologi penginderaan jauh terkait penilaian tingkat keparahan kebakaran telah banyak berkembang, salah satunya dengan metode Normalized Burn Ratio (NBR). Namun, penerapan metode tersebut perlu diverifikasi dengan pengukuran di lapangan (ground check) sehingga diharapkan informasi yang diperoleh lebih akurat dan efektif dalam upaya penilaian dampak kebakaran hutan dan lahan. Penelitian ini berfokus pada estimasi tingkat keparahan kebakaran lahan gambut di Kabupaten Siak, Provinsi Riau agar terciptanya langkah-langkah dalam upaya penanganan pascakebakaran, baik itu upaya rehabilitasi, evaluasi, dan penegakan hukum. Lokasi penelitian dilakukan pada lahan gambut terbakar di Kabupaten Siak, Provinsi Riau. Pengolahan data analisis citra dengan metode Normalized Burning Ratio (NBR) dilakukan pada bulan Mei hingga bulan Agustus 2021 di Laboratorium Kebakaran Hutan dan Lahan, Fakultas Kehutanan dan Lingkungan IPB. Hasil dari perhitungan metode Normalized Burning Ratio digunakan sebagai penentuan lokasi pengambilan data sampel di lapangan. Pengambilan dan pengukuran sampel di lapangan dengan metode fire severity, dilakukan pada bulan September tahun 2021. Berdasarkan hasil perhitungan Normalized Burning Ratio, Kabupaten Siak memiliki luasan tingkat keparahan kebakaran tinggi sebesar 93,33 ha, tingkat keparahan sedang hingga tinggi seluas 6.081 ha, tingkat keparahan sedang hingga rendah seluas 11.467 ha, dan tingkat keparahan rendah seluas 34.724 ha. Jika dibandingkan dengan hasil pengukuran di lapangan (ground check), metode fire severity menunjukkan hasil tingkat keparahan yang sama dengan metode Normalized Burning Ratio pada lahan dengan tingkat keparahan kebakaran tinggi., Fires that occur on peatlands have a very bad impact on human health and the environment. The impact that incurred because of these fires needs to be analyzed further. One of the approaches in assessing the impact of fires is the fire severity approach, which assesses the impact of fires on vegetation and soil properties. Remote sensing technology related to the assessment of fire severity has been broadly developed, one of the methods is the Normalized Burn Ratio (NBR). However, the application of this method needs to be verified with measurements in the field (ground check) in order to obtain more accuracy and effectiveness in assessing the impact of forest and land fires. This research focuses on estimating the severity of peatland fires in Siak Regency, Riau Province in order to create steps in post-fire management efforts, including rehabilitation, evaluation, and law enforcement efforts. The research location was conducted on a burning peat area in Siak Regency, Riau Province. Image analysis data processing using the Normalized Burning Ratio (NBR) method was carried out from May to August 2021 at the Forest and Land Fire Laboratory, Faculty of Forestry and Environment, IPB University. The results of the calculation of the Normalized Burning Ratio method are used to determine the location of field sampling. Data collection and measurements in the field sampling using the fire severity method was carried out in September 2021. Based on the results of the Normalized Burning Ratio
Keyword: Fire Severity, NBR, Peatland Fire, Remote Sensing

Judul: Optimization of Alginate-Chitosan Microcapsules Formation for Leydig Cells Encapsulation
Abstrak: Hypogonadism is a clinical condition characterized by low concentrations of testosterone. It is caused by malfunction of Leydig cells in producing testosterone. Encapsulation method will protect the transplanted cells from the immune system rejection. The aims of this study was to optimize the formation of microcapsules for Leydig cells encapsulation. The microcapsules were made of alginate and chitosan as the first and the second coating agents, respectively. The result showed that the minimum concentration of alginate was 1.5% (w/v) with a viscosity of 33.8 cPs, resulted spherical microcapsules with diameters of 230-270 µm. The optimum concentration of chitosan as the second coating agent was 0.5% (w/v), resulted spherical microcapsule with mechanical stability in 4 hours. Leydig cells can be trapped inside the capsule with a density that proportional with concentration of cells used in the encapsulation.
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