Judul: A monte carlo investigation of the power of white and breuschpagan tests on detecting regression heteroscedasticity
Abstrak: White and Breusch-Pagan Tests were designed to test whether the data violate the assumption of homoscedasticity in a linear model or not. In this research, a Monte Carlo Simulation was used to investigate the power as well as the consequence of failure of both tests in detection of heteroscedasticity as measured with Relative Efficiency (RE) of estimators between OLS and WLS. This research was focused on simple linear regression case and the variance function used was g(z, a) = I +a1 z", and the z was assumed as x. In this experiment, three factors were tried, the sample size or the ma"imum value of x, the proportion of contamination of error and the power of variauce fuuction. The simulation reveals that both tests have a similar pattern in the power due to the effects of three factors tried. However, the Breusch-Pagan Test always shows better power. The maximum value of x has increasing effect in the power of both tests and has interaction with power of the variance function. The proportion of contamination has non-linear effect on the power and has little interaction effect witll tile other factors. In general, the consequence of failure as measured with RE was the increase of RE as the power of both tests increased due to the increased of variance ratio between tile smallest and the largest value of the error variance yielded by tile variance function.
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Judul: Comparison Of SimulationExtrapolation, Regression Calibration And Instrumental Variable In Reducing The Bias Due To Measurement Error
Abstrak: The inability to accurately measure important variables complicates the statistical analysis of data when the purpose of inference is for the model defined in terms of the unobserved variables. In such situation, fitting the model directly to the observed data induces the bias estimates. For reducing the bias, some methods have been proposed such as Simulation-Extrapolation, Regression Calibration and Instrumen1al Variable. In this paper, the effects of measurement error on estimation)n linear and logistic regression will be demonstrated and the methods for bias rcd.uction will be compared. via simulation. The measurement error of predictors reduces the parameter estimate i.e. problem of attenuation. The corre1a1ion in predictors or the correlation in errors influences the magnitude and the direction of the bias. In general, Simulation-Extrapolation, Regression Calibration and Instrumental Variable can reduce the bias except for the structure of complex error in simple linear regression lnstrumental Variable tends more relatively stable on estimation with the increasing of measurement error compared with SimulationExtrapolation or Regression Cahbration estimation.
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Judul: Produksi Sirup Fruktosa dari Inulin Umbi Dahlia Dalam Reaktor Sinambung Unggun Terkemas Menggunakan Enzim Inulinase Imobil
Abstrak: Sirup fruktosa merupakan alternatif bahan pemanis lain yang kebutuhannya semakin lama semakin meningkat. Selain dari pati, sirup ini dapat juga diproduksi dari inulin yang berasal dari umbi dahlia (Dahlia pinnata Cav.) yang relatif mudah dibudidayakan di Indonesia. Gula cair dari inulin ini mempunyai banyak kelebihan dibandingkan gula cair dari pati, diantaranya rendemennya tinggi (sampai 97 persen) dan prosesnya singkat (hanya 1 tahap).
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