Judul: Isolasi Taurin Dari Cairan Empedu Sapi
Abstrak: Tamin atan asam 2-aminoetanasulfonat adalah asam amino bebas berwujud kristal putih pada slim kamar dengan titik leleh 300°C. Senyawa ini berperan penting dalam proses metabolisme hewan dan dimanfaatkan sebagai komponen aktif minuman berenergi, serta sebagai suplemen dalam formulasi makanan bayi. Taurin menyebar dalam setiap organ tubuh mamalia tennasuk pada empedu daIam bentuk berkonjugasi dengan asam empedu.
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Judul: Isolasi dan karakterisasi sifat-sifat fungsional protein ampas tahu
Abstrak: Ampas tahu merupakan hasil samping dari proses pembuatan tahu. Kadar protein ampas tahu cukup tinggi yakni sebesar 26.6% pada kadar air 9% (Direktorat Gizi dan Kesehatan, 1993). Kebanyakan industri tahu memanfaatkan ampas tahu dengan cara menjualnya kepada petemak, pedagang oncom dm tempe gembus. Namun pada saat ini pemanfaatan ampas tahu sudah mulai banyak digunakan dalam aplikasi pangan diantaranya untuk pembuatan tepung kaya serat dan protein, pembuatan cookies, sosis, dan nugget. Proses isolasi dan karakterisasi protein ampas tahu diharapkan mampu meningkatkan nilai tarnbah ampas tahu, mengetahui sifat-sifat protein ampas tahu dan sebagai upaya pengadaan bahan pangan berprotein.
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Judul: Which one use to overcome multicollinearity ? Ridge regression or principal component regression
Abstrak: In multiple linear regression the effect of nonorthogonality of the prediction vectors is to pull the least squares estimates of the regression coefficient away from the true coefficient that one is trying to estimate. Separating the effects of each factor of the regressors has been found to be difficult because of high correlation among independent variables. Although the multicollinearity problem has been recognized by many ways, ordinary least squares is still the main technique used in many fields, but the estimation of regression coefficient can present problems when the data vectors for the predictors are not orthogonal, or in this case are multicollinear. In using ordinary least squares, the regression coefficient may be unstable, too large in absolute value, and incorrect with respect to sign. Introduced biased estimation refer to unbiased one that measure the average closeness to the parameter being estimated corresponding to its mean square error (MSE). Ridge regression and principal component can produce better estimates by its own way than those given by ordinary least squares. It may well be preferred estimator since it will have larger probability of being close to true parameter value. Two of the biased regression methods, ridge regression and principal component regression will be applied into this research and discuss briefly for each of its properties. These methods have its particular idiosyncrasy. The biased regression methods attack the collinearity problem by computationally suppressing the effects of the collinearity. Ridge regression does this correctly by modifying the correlation matrix adding a biased constant driving through nonsingular matrix. Principal component regression attacks the problem by regressing Y on the important principal component and then parceling out the effect of the principal component variables to the original variables. Finally translated back the obtained variables into original variables yield the same sign and nearly the same coefficients for both methods.
Keyword: Regresssion analysis