Judul: Komposisi Kimia Tambelo (Bactronophorus Sp.) Dan Karakteristik Produk Hasil Fermentasinya.
Abstrak: Tambelo (Bactronophorus sp.) adalah hewan penggerek kayu yang dikelompokkan kedalam filum moluska. Tambelo hidup pada batang kayu bakau yang telah mati dan mengalami proses pembusukan. Pengalaman empiris masyarakat pantai Sulawesi Tenggara dan beberapa hasil penelitian menunjukkan tambelo memiliki nilai gizi yang tinggi sehingga bermanfaat bagi kesehatan. Tambelo jenis Bactronophorus sp. di pantai Sulawesi Tenggara ditemukan hidup pada bakau Rhizophora sp., Bruguiera sp. dan Sonneratia sp. Tambelo mudah membusuk dan pengolahan tambelo belum banyak dilakukan sehingga tingkat pemanfaatannya rendah. Oleh karena itu pembuatan tambelo fermentasi dapat menjadi alternatif pemanfaatan hewan ini. Fermentasi secara tidak spontan memberikan kualitas fisika-kimia dan mikrobiologi produk lebih baik dibanding fermentasi spontan dan bakasang berpotensi sebagai starter untuk membuat produk fermentasi. Tujuan penelitian ini adalah menentukan profil berat dapat dimakan (BDD), komposisi kimia, asam amino, asam lemak dan kelompok senyawa kimia tambelo yang hidup pada bakau Rhizophora sp., Sonneratia sp. dan Bruguiera sp. di perairan pantai Sulawesi Tenggara, membuat produk tambelo fermentasi dan menentukan profil komposisi kimia dan asam amino tambelo fermentasi. Penelitian ini dilakukan pada bulan Januari 2014 hingga Agustus 2014. Penelitian dilaksanakan dalam tiga tahap. Tahap pertama adalah karakterisasi daging tambelo yang meliputi analisis bagian dapat dimakan (BDD), komposisi kimia, asam amino, asam lemak, dan kelompok senyawa kimia. Tahap kedua adalah pembuatan produk fermentasi tambelo. Nilai pH, kadar NaCl, total mikroba dan total bakteri asam laktat (BAL) dianalisis setiap minggu hingga 4 minggu fermentasi. Tahap ketiga adalah karakterisasi produk tambelo fermentasi yang meliputi analisis komposisi kimia dan asam amino. Tambelo yang hidup pada bakau Rhizophora sp. memiliki kadar protein dan kadar lemak lebih tinggi dibanding tambelo pada Sonneratia sp. dan Bruguiera sp. Selama fermentasi nilai pH menurun dan kadar NaCl cenderung stabil. Total mikroba dan bakteri asam laktat (BAL) meningkat sampai minggu kedua, dari minggu kedua sampai minggu ketiga cenderung stabil, kemudian dari minggu ketiga sampai minggu keempat mengalami penurunan. Sebelum fermentasi tambelo megandung kadar air 82,51 % dan setelah fermentasi 82 %. Kadar abu sebelum fermentasi 2,27 % dan setelah fermentasi 1,48 %. Kadar protein sebelum fermentasi 8,21 % dan setelah fermentasi 9,50 %. Kadar lemak sebelum fermentasi 3,34 % dan setelah fermentasi 0,42 %. Kadar karbohidrat (by different) sebelum fermentasi 3,67 % dan setelah fermentasi 6,60 %. Persentasi asam amino bebas pada tambelo fermentasi cenderung meningkat dibandingkan sebelum fermentasi. Mikroba yang ada pada bakasang mampu menghidrolisis komponen yang ada pada tambelo sehingga bakasang dapat digunakan sebagai starter untuk fermentasi tambelo.
Keyword: bakasang, fermentasi, tambelo

Judul: Chemical Composition and Identification of Antioxidant Compounds from the Extracts of Tambelo (Bactronophorus thoracites)
Abstrak: Tambelo (Teredinidae) is consumed freshly by local people in Papua without removing the digestive tracts. This study aimed to investigate the chemical composition of fresh tambelo, to conduct antioxidant and phytochemistry tests, and to identify the compound of active antioxidant obtained from selected fractionated extract. The research consisted of two stages. The first stage involved the analyses of proximate, fatty acid, amino acid and mineral. The second stage was the extraction of active materials by means of maceration. The maceration result was evaporated and partitioned with a solvent of n-hexane and ethyl acetate. Next, the extract underwent phytochemical and antioxidant tests (20, 40. 60, and 80 ppm) with DPPH method applying BHT and vitamin super ester C as the standard with a concentration of 4, 6, 8 and 10 ppm. Finally, the identification of fresh antioxidant compound was carried out using LC-MS. The composition of fresh tambelo divided into moisture 82,72±0,01%, protein 7,21±0,31%, fat 0,28±0,04%, ash 2,07±0,27%, and carbohydrate (by difference) 7,72±0,62%. The composition of dried tambelo was moisture 6,63±0,01%, protein 42,77±2,01%, fat 14,27±0,22%, ash 5,88±1,04%, carbohydrate (by difference) 30,45±2,83%. The protein of tambelo contained nine essential amino acids and eight non essensial amino acids. It had seven saturated fatty acids and eight unsaturated fatty acids. It contained calcium of 3532,46 ppm and phosfor of 2363,06 ppm. The highest antioxidant activity was found in the crude extract of ethyl acetate with IC50 of 15 ppm. The highest antioxidant activity obtained by column fractionation was the 9th fraction with IC50 of 8.87 ppm. Phytochemical test, described the crude extract of tambelo contained a group of alkaloid, flavonoid, steroid and triterpenoid. MarinLit database (Blunt and Blunt 2008), 9th fraction was similar to farnesic acid glyceride, sesquiterpenoic acid glyceride and labdane diterpenoid.
Keyword: 

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