Judul: Upaya memperpanjang umur simpan tempe dengan metode pengeringan dan sterilisasi
Abstrak: Tempe merupakan makanan tradisional Indonesia yang dikonsumsi oleh hampir semua lapisan masyarakat. Tempe mengandung komponen-komponen gizi yang tinggi, seperti protein dan vitamin B12. Tempe juga diketahui mengandung senyawa antioksidan yang diidentifikasi sebagai isoflavon. Senyawa ini diyakini mempunyai peranan dalam meredam aktivitas radikal bebas, sehingga bermanfaat bagi pencegahan kanker seperti halnya karotenoid, vitamin E dan vitamin C. Tempe pada umumya mempunyai daya simpan yang relatif singkat. Penelitian ini bertujuan untuk memperpanjang umur simpan tempe sehingga jangkauan pendistribusiannya dapat lebih luas. Metode yang digunakan dalam penelitian ini adalah pengeringan dengan batch fluidized solar dryer, pengeringan dengan oven, dan sterilisasi.
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Judul: Pengaruh penambahan bumbu dan proses pengolahan untuk meningkatkan daya terima dan daya simpan tempe
Abstrak: Tempe merupakan makanan yang dibuat dari kacang kedelai yang difermentasikan menggunakan kapang Rhizopus. Produk ini dikonsumsi oleh semua lapisan masyarakat, dengan konsumsi rata-rata pertahun 5.2 kg/kapita. Pada umumnya tempe memiliki umur simpan dua hari setelah itu akan mengalami kerusakan, sehingga perlu dilakukan penelitian mengenai cara pengawetan tempe.
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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