Judul: Model prediksi awal musim hujan di Pulau Jawa dengan menggunakan informasi suhu muka laut di kawasan Pasifik dan India
Abstrak: The rainfall variability is one of an important role to play onset of wet season. This research aims to analyze that SST (Sea Surface Temperature) exerting an influence on rainfall onset over Java. The significant scale (15°S – 15°N; 80°E- 100°W) of SST patterns are observed to derive a potential predictor rainfall onset over Java. The onset wet season is define as the first 10-day that receive at least 50 mm followed by 2 consecutive 10-days. In Java generally it starts from 1 September. In this study, The regression Multivariate method was offered to develop a rainfall onset model prediction based on SST circulation patern. The principal component and regression technique are improved to achieve a better models and cross validation technique were applied to validate models. Domain predictor of models were derived using spatial correlation analysis result between Rainfall onset data each ZOM over Java and SST anomaly from Indian Ocean to Pacific Ocean during 1978-2007 . There are 28 from 30 ZOM which have potential predictors that be trained to models. The high spatial coherence of the rainfall onset is SST pattern at Juni-Juli-August that represent SST on eastern equatorial Pacific as characteristic of El Nino Southern Oscillation (ENSO), SST on Western Sumatera Island as characteristic of Indian Ocean Dipole Mode (IOD) and SST on around Java region as Characteristic of local condition. Three representative correlation patterns of Java Rainfall onset with SST Indian-Pacific area are investigated that clarify of ENSO, IOD and local condition. Verification result for those models showed promising skill prediction during test in year of 2008 with standart deviation 10 days. In Java generally, skill prediction when rainfall onset advanced exhibited better result than skill prediction when it delayed. The Indonesian ocean area that has local characteristic have influenced better rainfall onset over Java than others. It indicated that models which developed using predictor of Indonesian SST have better skill prediction than SST of Indian or pacific ocean area. However, predictor which has combination domain area of Indonesian SST and Pacific have main influenced rainfall onset over Java. It can be explained that 18 ZOM’s model have been using predictor from those domain.
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Judul: Prediksi Awal Musim Hujan di Provinsi Sulawesi Selatan Menggunakan Data Anomali Suhu Muka Laut
Abstrak: The Province of South Sulawesi is one of the centers for national paddy production with 7% contribution from total paddy production in national level. The increasing of paddy production depends on the water availability. Moreover, the water availability is always associated with the onset of rainy seasons, because if an area has the forward or backward of onset of rainy season, it will influence the water availability and crop calendar. In order to onset of rainy seasons, to reduce the farmer’s loss and to protect the food stability level in Indonesia, it needs to identified the areas which have the sensitivity for the onset of rainy season’s variability to climate control factors like ENSO and IOD. This research has been conducted to study the correlation between onset of rainy seasons (AMH) in South Sulawesi and sea surface temperature anomaly (AnoSML) in Pacific Ocean and Sulawesi Sea, to determine the domain of sea surface temperature predictor which has influence the onset of rainy seasons in South Sulawesi and to develop the onset of rainy season model prediction in South Sulawesi based on the sea surface temperature anomaly in Pacific Ocean and Sulawesi Sea. This research has been conducted using daily rainfall data during 30 years (1980-2010) from rainfall stations in South Sulawesi, sea surface temperature anomaly data for 4 domains i.e. Nino 3 region, Nino 3.4, Nino 4 and Sulawesi Sea on June, July, August and September (JJAS) during 30 years. The first analysis of data was conducted with the examination of observation daily rainfall data and selection of rainfall stations which are used for the development of the rainy season onset prediction model. Further analysis was conducted to determine the onset of rainy seasons using Moron’s method (five days of daily rainfall data/pentad analysis). The result of pentad analysis was used to calculate Principle Component Analysis (PCA) which was used to determine the cluster of rainfall stations. The correlation analysis was then calculated between the onset rainy seasons on each cluster and AnoSML data on JJAS. The last analysis was conducted for development of onset rainfall season model prediction and verification of the model. Based on the checking of observation daily rainfall data with the data availability >70%, there were 45 chosen stations for onset of the rainy season analysis. The result of AMH analysis showed that the average of AMH for whole stations was on the 348th Julian Date (JD) or on 14th December. The highest AMH was obtained at Stasiun BPP. Panincong (PNCG) in Soppeng District with 473th Julian Date or on 18th April. Otherwise, the lowest AMH was obtained at Stasiun BPP. Keera (KERA) in Wajo District with 278th Julian date or on 5th October. The result of PCA analysis showed that there were six PCs which were explained variability of data ± 80%. Based on the PC clustering, there were 3 clusters of rainfall stations. Cluster 1 has 13 rainfall stations which are spread in 9 districts i.e. Bantaeng District, Bulukumba, Enrekang, Gowa, Luwu, Maros, Pinrang, Soppeng and Wajo District. On Cluster 2, there are 10 rainfall stations
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Judul: Case Study of Gallbladder Mucocele and Treatment Used In Small Animals
Abstrak: Gallbladder mucocele (GM) is defined as distention of the gallbladder caused by an inappropriate accumulation or deposition of high concentrations of bile. The purpose of this case study is to study GM conditions in small animals and to report the clinical sign and characteristics of GM through the sonogram interpretation and blood chemistry test evaluation, and studies related to the therapy given and other treatments recommended. A 14-year-old Toy Poodle dog has been diagnosed with severe GM and cholecystitis. No pain signs were shown during the physical examination as asymptomatic is a common characteristic in the early stage of biliary related diseases. In this study Abdominal ultrasonography interpretation and blood chemistry evaluation was conducted in 2021-2022 and analyzed as a secondary data source. Ultrasonography results showed presence of hyperechoic, immobile deposits in gallbladder accompanied by wall thickening and enlarged in size, followed by a significant increase in the enzyme alkaline phosphatase (ALP). This study has summarized mainly the diagnosis and treatments of GM in small animals and suitable alternatives treatments were recommended to encounter the GM conditions in small animals. The effectiveness of combined therapy shows the positive impact on the patient, the condition of GM has been under control.
Keyword: ultrasound, gallbladder, biliary sludge, abdominal ultrasonography