Judul: Application of regCM3 output for drought analysis in Seluna Sub Basin
Abstrak: Assessment of drought characteristics requires long historical climate data. In many cases, long historical data is hardly available. Climate dynamic model is very potential to be used for reconstructing long historical climate data. This study aims to reconstruct daily climate data using climate model RegCM3 and to assess the characteristic of drought occurrence in rice paddy using the reconstructed data from the climate model. The drought analysis was done using water balance model. The result of the analysis suggests that the development of correction factor for RegCM3 is required before the reconstructed data is used for drought analysis. The pattern of drought generated using the reconstructed data is similar to that of the observed ones. The result of analysis indicates that the rice start suffering from drought when the soil water has dropped below 30% of field capacity and this condition occurs mostly during August to October. This study recommends the use of RegCM3 output for climate impact analysis in areas where daily climate data is limited or not available.
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Judul: Statistical Downscaling of GCM Data using Support Vector Regression to Predict Monthly Rainfall in Indramayu.
Abstrak: The knowledge about weather and climate pattern, especially rainfall is required by many sectors such as, agricultural, plantation, transportation, and so on. Recently, the model that is used to observe the impact and to predict the climate change is the global circulation model (GCM). However, the current GCM-resolution data is too low and it is difficult to predict the local climate pattern that requires high resolution. However, it is possible to obtain regionalscale information if it is combined with statistical downscaling (SD) methods. The main objective of this research is to develop SD models by using support vector regression (SVR) in forecasting monthly rainfall in Indramayu, in order to get the accurate climate information based on GCM data. The results of this research showed that overall, the model is good enough to predict rainfall with normal conditions. But for extreme circumstances, although the prediction model was able to follow the pattern of the observational data, but the value of the resulting predictions have not managed to predict accuratelly the actual observed values. Variations of the evaluation of estimated results by the model for 13 rain stations in Indramayu district showed that the location of rain stations in certain areas can influence and determine the accuracy of the monthly rainfall forecast. Rain observations points located farther from the sea tend to have better estimation results than the observation points located close to the sea.
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Judul: Trichomonas Gallinae Penyebab Trichomonosis Pada Unggas
Abstrak: Trichomonas gallinae adalah protozoa yang bergerak aktof dengan keempat flagella yang mempunyai layar dan pada salah satu sisinya terdapat membran seperti sirip ikan yang berombak. Spesies dari genus Trichomonas ini mempunyai arti penting pada unggas, karena dapat menyebabkan infeksi pada alat pencernaan bagian atas.
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