Judul: Proyeksi Curah Hujan Masa Depan di DAS Cisadane menggunakan Teknik Statistical Downscaling pada Luaran Model Iklim Global (GCM)
Abstrak: The changes of pattern and duration of the rainy season due to climate change affect water availability for agriculture sector, particularly in the Cisadane watersheds. Climate change projections particularly on local scale rainfall in the region are greatly needed. In this case the output of Global Circulation Model (GCM) can be used to project the local scale rainfall by using downscaling techniques. The result showed that the downscaling models developed by using simple regression analysis has a relatively small determination and correlation coefficients respectively ranging from 0 to 0.13 and from –0.183 to 0.366. In order to obtain better results, Principle Component Analysis (PCA) was used to transform and reduce the variables from the GCM outputs namely CSIRO, GFDL, and CGCM3. Six principle component (PC1-PC6) were selected from each GCM data, and were then used to build multi-linear models with observation data. This analysis is called principal component regression (PCR). It is found that PCR reproduced better results for almost all GCMs in comparison with the simple regression results. This study indicates that CSIRO produces better downscaling model compared to other GCMs used in this study. This can be seen from the highest coefficient of determination (0.533) and correlation (0.73) on Citeko Station resulted by the model, which was followed by CGCM3 and GFDL at the same station. Model validation using root mean square error (RMSE) and correlation showed that the resulted downscaling models based on PCR are significant at 95% confidence level. Future projections on each GCM based on the average of all stations showed an increase in mean rainfall values compared to the baseline data, where the highest percentage of increase (around 21.63%) was found in CGCM3. Meanwhile, based on the average of all GCMs, Station Citeko was projected to have the highest increase in future rainfall (11.6%). The average percentage of all increases between current and future rainfall is 9.04%. If seperated based on season, each model showed an increase of mean rainfall value during wet season and a decrease during dry season, except for CGCM3.
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Judul: Kuantifikasi Perubahan Curah Hujan Ekstrem dan Respon Hidrologi DAS dengan Menggunakan  Data  Proyeksi  Iklim  Beresolusi  Tinggi
Abstrak: Climate change has impacted various sectors, including water resources. The extent of the potential impact of climate change on hydrometeorological disasters has prompted a special study to manage extreme climate change, especially precipitation. Objectives of the study are to examine the reliability of high- resolution climate model outputs in representing historical and present extreme rainfall conditions and hydrological responses at watershed scale and analyses the hydrological response (flow discharge) to extreme precipitation in the future. The study used rainfall from high-resolution climate model (RCM), i.e. CORDEX (Coordinated Regional Climate Downscaling Experiment Southeast Asia) and NEX-GDDP (NASA Earth Exchange Global Daily Downscaled Projects) from three time periods, i.e. past (1981-2005), present (2006-2020), and future (2021- 2045) for Ciliwung watershed. The study applied the quantile mapping method to correct the bias of the RCM data, the hydrology response to rainfall used HEC- HMS model, and relationship between extreme streamflow causing flood with rainfall used regression model. The results of the analysis show that the corrected RCM outputs can represent the observed rain conditions quite well for most of the models, except for the ACCESS1-0 RCP8.5 model. Bias correction using the QM method can reduce the bias value of the model in historical and present periods, for both the RCP4.5 and RCP8.5 climate scenarios. The best performing models are ECEarth, CSIRO, MPI, and CNRM. Most of the models show good performance in representing extreme rainfall conditions. Furthermore, the results of the regression analysis show that extreme streamflow significantly associated with rainfall events one and two days before. Using the regression equations, it is indicated that the annual maximum discharge at the Katulampa and Depok water estimators will increase in the future according to the climate scenario RCP4.5, otherwise in the climate scenario RCP8.5. The frequency of extreme discharges is also predicted to increase in future.
Keyword: bias correction, climate change, discharge, precipitation

Judul: Studi Kasus Liver Neoplasia pada Anjing Shih Tzu
Abstrak: Liver neoplasia is the excessive and uncontrolled replication of hepatocytes that forms nodules visible in ultrasonography. The purpose of this study is to study and discuss the characteristic, diagnosis and treatment of liver neoplasm through the interpretation of ultrasonography and hematology in a Shih Tzu dog. Ultrasonography is conducted with a Chison Q8 ultrasound machine with a 5 to 7 MHz frequency convex probe on lateral recumbency. The blood cells, liver enzymes and nodules sizes were the main parameters in this study. The results in the period of three years from 2021 to 2023 were interpreted and supported with secondary data sources. The Shih Tzu dog is 14 years old in the year 2023 with a body weight of 5.21kg. No obvious clinical signs were observed during previous examinations. However, lethargy, vomiting and anorexia were recorded in its latest examination. Thrombocytosis, granulocytosis, high liver enzymes and hypoglycemia, which are some of the neoplastic clinical manifestations were also presented by this patient. Besides, liver neoplasm, spleen neoplasm and biliary sludge were the sonogram findings of this patient. The liver and spleen neoplasm was observed stable, while the biliary sludge volume fluctuated. The treatment strategy recorded is Ondansetron, Samylin®, Ornipural and Ursodeoxycholic acid.
Keyword: Blood biochemistry profile, Hematology, Liver Neoplasia, Shih Tzu, Ultrasonography