Judul: Ketahanan Sperma Dalam Saluran Kelamin Betina Untuk Membuah Sel Telur Serta Pertumbuhan Dan Perkembangan Embrio Pada Ayam Kedu (Gallus demosticus)
Abstrak: Penelitian tentang ketahanan sperma dalam saluran kelarnin betina untuk membuahi sel telur serta pertumbuhan dan perkembangan embrio ayam Kedu dilakukan di Laboratorium llmu Produksi Ternak Unggas, Fakultas Peterriakan dan Laboratorium Embriologi, Fakultas Kedokteran Hewan, Institut Pertanian Bogor mulai bulan Oktober 1991 sampai Maret 1992. Ternak yang digunakan adalah ayam Kedu betina urnur 12 bulan sebanyak 32 ekor dan ayam Kedu jantan umur 18 bulan sebanyak enam ekor. Semen jantan dievaluasi volume, warna, pH, konsistensi, gerakan massa, gerakan individu dan konsentrasi spermatozoanya. Untuk mengetahui lamanya daya tahan sperma dalam saluran kelamin betina dan fertilitas dilakukan inseminasi menggirnakan perlakuan semen yang diencerkan memakai larutan Ringer's dengan dosis inseminasi 0,l ml.
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Judul: Pengaruh berbagai macam pengecer semen dan dosis inseminasi buatan terhadap fertilitas dan daya tetas telur pada ayam buras
Abstrak: Penelitian ini dilakukan di Laboratorium Balai Penelitian Ternak Ciawi Bogor dan Kelompok Peternak Unggas Mekar Desa Karangkamulyan Kecamatan Cijeungjing Kabupaten Ciamis, mulai bulan Desember 1993 sampai Mei 1994. Tujuan penelitian adalah untuk mengetahui pengaruh pengencer semen NaCl kuning telur, Ringer, air kelapa kuning telur terhadap motilitas sampai 40% dan persentase hidup spermatozoa pada suhu 5°C dan 25°C; mengetahui hasil IB terhadap fertilitas dan daya tetas telur dengan menggunakan ber- bagai tingkat dosis spermatozoa dalam pengencer tersebut diatas. Sepuluh ekor ayam buras jantan (peranakan Sentul) digunakan untuk penelitian di Laboratorium dengan pengencer NaCl kuning telur (4:1); Ringer; air kelapa kuning telur (4:1) dengan dosis 100 juta spermatozoa/ml. Pengamatan kualitas semen secara makroskopis meliputi volume, bau, warna, konsistensi dan pH, serta secara mikroskopis meliputi gerakan massa, motilitas dan persentase hidup spermatozoa, yang selanjutnya dilakukan..dst
Keyword: Insemination, chicken housing, Ayam buras

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