Judul: Analisis Dekomposisi Nilai Singular Pada Data Indikator Iklim dan Kebakaran Hutan di Indonesia
Abstrak: Kebakaran hutan dan lahan (karhutla) merupakan bencana yang terjadi di Indonesia. Salah satu indikator iklim lokal yang memengaruhinya adalah curah hujan. Indikator curah hujan akan diturunkan menjadi hari tanpa hujan dan anomali curah hujan. Ketiga indikator iklim ini akan dianalisis bersama luas area terbakar, emisi karbon, dan hotspot secara spasial dan temporal. Analisis spasial dilakukan dengan mereduksi dimensi waktu pada keenam indikator, sedangakan analisis temporal dilakukan dengan mereduksi dimensi lokasi pada keenam indikator. Proses pereduksian dimensi dilakukan dengan Dekomposisi Nilai Singular. Hasilnya, luas area terbakar merupakan indikator terbaik yang mampu menangkap karhutla di Indonesia tahun 1997-2020. Sementara itu, indikator emisi karbon merupakan yang paling baik dalam menangkap karhutla di Indonesia tahun 1999-2020. Indikator iklim terbaik dalam menjelaskan kasus karhutla adalah hari tanpa hujan karena memiliki nilai korelasi paling tinggi terhadap luas area terbakar, emisi karbon, dan hotspot., Forest and land fires are disasters that occur in Indonesia. One of the local climate influencing indicators forest and land fires is rainfall. Rainfall indicators will be simplified to dry spell and rainfall anomalies. These three climate indicators will be analysed along with the burned area, carbon emissions, and hotspots spatially and temporally. The spatial analysis is carried out by reducing the time dimension on the six indicators, while the temporal analysis is carried out by reducing the location dimension on the six indicators. The dimension reduction process is done by the Singular Value Decomposition. As a result, the burned area is the best indicator capable of capturing forest and land fires in Indonesia in 1997-2020. Meanwhile, carbon emission indicators are the best in capturing forest and land fires in Indonesia in 1999-2020. The best climate indicator in explaining the case of forest and land fires is a dry spell because it has the highest correlation value to the burned area, carbon emissions, and hotspots.
Keyword: indicator, rainfall, forest and land fires, singular value decomposition, correlation

Judul: Karakterisasi Indikator Global terhadap Pola Bersama Luas Area Terbakar dan Curah Hujan di Indonesia
Abstrak: Tujuan dari penelitian ini adalah menerapkan metode combined EOF berbasis Singular Value Decomposition (SVD) dengan menganalisis data luas area terbakar, indikator global (Indian Ocean Dipole, El Nino dan La Nina), dan curah hujan di Indonesia. Metode yang digunakan dalam penelitian ini adalah Empirical Orthogonal Function (EOF) berbasis Singular Value Decomposition (SVD) untuk mereduksi matriks data ke dalam program komputer menggunakan software. Metode ini bertujuan untuk menentukan pola–pola dominan pada data luas kebakaran dan curah hujan baik secara spasial maupun temporal. Hasil dari penelitian ini yaitu didapatkan sinyal dominan yang mempengaruhi kebakaran di setiap wilayah. Kata kunci: Curah hujan, Dekomposisi nilai singular, Empirical orthogonal function (EOF), ENSO dan IOD, Kebakaran hutan, Forest fires in Indonesia are influenced by several indicators, including the area burned, rainfall, and global indicators (ENSO and IOD). The purpose of this study is to apply the combined EOF method based on Singular Value Decomposition (SVD) by analyzing data on the burned area, global indicators (Indian Ocean Dipole, El Nino, and La Nina), and rainfall in Indonesia. The method used in this research is Empirical Orthogonal Function (EOF) based on Singular Value Decomposition (SVD) to reduce the data matrix into a computer program using software. This method aims to determine the dominant patterns in the data of fire area and rainfall both spatially and temporally. The results of this study shows the dominant signals which affect fires in each regions.
Keyword: Empirical orthogonal function (EOF), ENSO and IOD, Forest fires, Rainfall, Singular value decomposition

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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