Judul: Dehydration of tempeh with traditional spicy using sunbeam food dehydrator type DT5600
Abstrak: Tempeh is one of the most popular traditional food consumed by Indonesian people for many years. The addition of spicy was one of the preservation methods that could expand the shelf life until four weeks. The performance test is needed to determine the effect of temperature through quality parameter of the best slice spicy tempeh. The objectives of this research were to conduct the performance test of Sunbeam Food Dehydrator DT5600 and to determine the effect of temperature through the quality parameter after the addition of spicy to tempeh. The drying temperature of 75 °C had shorter drying time and had the larger drying rate compare with the temperature of 55 °C or 35 °C. The spicy addition treatment also had the effect on drying rate and drying efficiency, where with the addition of spicy would increase its value. Consumption drying energy was around 10.6 – 27.5 MJ/kg moisture content. The protein concentration was more than 40%. Based on the hedonic test and laboratory test, panelist tend to like and no microbial contaminants.
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Judul: The Impact of Blanching and Vacuum Packaging to The Shelf Life of Fresh Seasoned Tempe
Abstrak: Tempe is an indigenous fermented food from Indonesia, prepared by the action of molds, Rhizopus sp., on cooked soybeans. In 2012, up to 60% of soybean production went to tempe industry with consumption of tempe reaching 8.5 kg per person per year in Indonesia. However, the export of tempe seems still impossible due to its perishable characteristic whose shelf life is very short. Preblanching and vacuum packaging were expected to extend the shelf life of tempe. This research was aimed to study the application of blanching and vacuum packaging on the shelf life of fresh-seasoned tempe. Steam blanching of 80 oC for three minutes was selected from pre-investigation for pre-treatment of the tempe without inducing cooked-tempe characteristic. The result of main research revealed that steam blanching and vacuum packaging were able to extend the shelf life of fresh-seasoned tempe for two days in room temperature (23-24 oC), 32 days in refrigeration temperature (4-6 oC), and 49 days in chilling temperature (0-4 oC). The pH of tempe was found increasing during storage with texture getting overstuffed or tender during storage.
Keyword: Bogor Agricultural University, vacuum packaging, storage temperature, shelf life, Fresh-seasoned tempe

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