Judul: Metode Regresi Komponen Utama, Regresi Kuadrat Terkecil Parsial, dan LASSO pada Data Kemiskinan Hasil Olahan Susenas 2012
Abstrak: Multicollinearity is a problem that is arise in multiple linear regression. Multicollinearity lead testing and estimating coefficient regression models become invalid because it produces a large variety. Methods that can be used to overcome multicollinearity in the data in among these are PCR, PLS, and LASSO. PCR and PLS forming independent new components to overcome multicollinearity. Both method previously unable to do the screening variables. LASSO does the screening variables by shrinking appropriate coefficient value of zero. The result showed the best model of the three based on RMSE value produced by LASSO method, and based on RMSEP value produced by RKU method. Difference in value of error for the three method are not much different.
Keyword: Bogor Agricultural University (IPB), PLS, PCR, Multicollinearity, LASSO

Judul: Kajian metode pendugaan pada model regresi dengan peubah penjelas bersifat acak
Abstrak: Regression analysis is a statistical method to evaluate the relationship between a variable with other variables. Model I regression analysis describes the one-way relationship between variable X and variable Y with the value of X as fixed variable or measured without error. Model I regression analysis uses Ordinary Least Square (OLS) as an estimation method. Model II regression analysis is a regression model with predictors variable that becomes a random variable. There are two estimation methods of model II regression analysis, ordinary least product regression (Model IIA) and major axis regression (Model IIB). The convenience of using model I regression analysis with OLS estimation method causes many researchers to use this model as a model regression analysis with random predictor variables. The purpose of this study is to compare model I regression analysis (OLS estimation method) and model II regression analysis (ordinary least product estimation method and major axis regression estimation method). The data used in this research are simulation data where response variable (Y) and predictor variable (X) are random. The result of this study showed for predictor variable is random, ordinary least product regression is the best estimation method compared to the other methods because it produces the smallest value of bias and the smallest value of mean square error. In this condition, OLS can be used for the estimate parameter of simple linier regression model if the correlation value between predictor variable (X) and response variable (Y) is high (r ≥ 0.9).
Keyword: Bogor Agricultural University (IPB), Model IIB, Model IIA, Model I, mean square error, correlation

Judul: Studi Komparatif Saluran Pencernaan Parkit (Melopsittacus undulatus) dengan tinjauan Khusus terhadap Fungsi Tembolok (Telaah Pustaka)
Abstrak: The structure of the digestive tract of Budgerigar (Melopsittacus undulatus) is generally the same as the digestive tract of the other avian, which is cranially start by a pair of beaks down to ventrocaudal and ends by the cloaca. The characteristics of the digestive tract of Budgerigar are in form of its beaks, tongue, crop, stomach, and intestine, which are adapted with the type of food intake. Crop (ingluvies) is an expansible ventral wall of oesophagus with its function as storage and softening chamber. Budgerigar's crop also has the function for softening and regurgitating pellets or food for their young.
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