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: Downscaling Methodology Development Using Arftificial Neyral Network (Case Study of Indramayu’s Rainfall).
Abstrak: The unexpected climate change results a long period wet and dry so it makes many agricultural areas damage. This is cause the farmers failed to harvest so the production of food will be decreased. To solve this problem, we need a model that can estimate the climate and rainfall so it can determine the suitable cropping pattern with the climate. Statistical downscaling modeling commonly used to model the changes of the weather. This study develops a statistical downscaling model that use artificial neural network with some of GCM data as an input in training. In this study, the GCM data is input for training. Before training this data is grouped into 5 groups. The results obtained indicate that some of the GCM can approach the average of monthly rainfall. However, in some extreme point, the result have not managed to reach and close to results of observation. The best results obtained with the correlation Bondan station at 0.4976 and the worst results obtained Krangkeng station with a correlation of 0.3704. In this study also can be seen that the estimators can be influenced by the location of the observation. The location is adjacent to the sea tend to have the results of a relatively lower correlation compared with the location that far from the sea.
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Judul: Karakteritsik kimia dan organoleptik tablet effervescent putih telur bersitarasa lemon dengan konsentrasi effervescent mix yang berbeda
Abstrak: Egg is an animal origin food product which has high nutritional value especially protein. Cholesterol content of eggs is only found in egg yolk, on the other hand albumen does not countain cholesterol at all but high content of protein, so it can be used as a free cholesterol-protein sources. The application of albumen as egg instant drink effervescent tablet can be an alternative of protein source for people who need free-cholesterol diet. It can also become an egg product diversification.
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