Judul: Perbandingan Model Identifikasi Daerah Bekas Kebakaran Hutan dan Lahan di Kalimantan Barat.
Abstrak: West Kalimantan is one of the provinces in Indonesia which is vulnerable to forest and land fires. One of alternative method that could be used to determine the burned area is by using remote sensing images, e.g. MODIS (Moderate Resolution Imaging Spectroradiometer) images. This research aimed to compare two identification model of burned area of the forest and land fires by remote sensing and to analyze the appropriate model used to be applied in Indonesia specifically in West Kalimantan using MODIS images. This research analyze the use of identification model by using vegetation index of Normalized Difference Vegetation Index (NDVI) and by using fire index of Normalized Burn Ratio (NBR). The result shows that both of the models provide good capability to detect burned area. However, NBR model has higher accuracy of 66.02% compared to NDVI of 64.02%. Therefore, the most appropriate identification model to be used at West Kalimantan by using MODIS image is the NBR model.
Keyword: Burned area, MODIS images, NBR

Judul: Pemanfaatan data READY-ARL NOAA dan CMORPH untuk pengembangan model risiko kebakaran hutan dan Lahan di Kalimantan Tengah
Abstrak: Land and forest fires are one of the many causes of land degradation in Central Kalimantan. The utilization of remote sensing data, particularly READY-ARL NOAA and CMORPH data, is helpful in providing climate observation data. The objectives of this study are: 1) to analyze the relationship between the surface observation data and the READY-ARL NOAA and CMORPH (CPC Morphing) data by using Partial Least Square (PLS) Method to extract climate data from the satellite, 2) to develop the FDRS (Fire Danger Rating System) indices by using READY-ARL NOAA, CMORPH and hotspot data derived from the satellite data, 3) to develop an estimation model for burned area from hotspot, rainfall condition, and FDRS indices, and 4) to develop fire risk prediction model. The result of this study indicates that the READY-ARL NOAA and CMORPH data have the potential to make climate data estimation and are relatively good as FDRS (SPBK) data input. The use of PLS method is much better in generating a model estimation than simple regression. Precipitation accumulation for two months prior to fire occurrence and drought condition have correlation with the burned area. There is a correlation between the total number of fire hotspot and a series of days without rain around one to two months prior to fire occurrence. In addition, this study also found that the burned area in Central Kalimantan will increase if the drought code exceeds 500 point. Burned area can be estimated by using the following formulas: Burned Area (Ha) = 5.13 – 21.7 (CH2bl – 93) (R-sq = 67.2%) and this formula: Burned Area (Ha) = -62.9 + 5.14 (DC – 500) (R-sq = 58%) where CH2bl = precipitation accumulation for two months prior to fire occurrence and DC = drought code. The forecasts of fire occurrence probability can be determined by using a precipitation accumulation for two months prior to fire occurrence and Monte Carlo simulation. Efforts to anticipate and address the fire risk should be carried out as early as possible, i.e. two months in advance if the probability of fire risk has exceeded the value of 40%.
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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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