Judul: Perilaku Reproduksi dan Karakteristik Mikrohabitat tempat Bertelur Burung Gosong (Megapodius reinwardtii Dummont 1823) Di Taman Buru Pulau Moyo
Abstrak: Burung gasang (Megapodius reinwardtii) merupakan jenis burung terestrial yang selalu berpasangan sepanjang hidupnya. Burung ini dilindungi berdasarkan SK Menteri Kehutanan No. 882/Kpts-II/1992 tanggal 28 September 1992. Penyebaran satwa ini hanya terbatas di wilayah Indonesia bagian timur.
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Judul: Studi interaksi antara komodo (Varanus komodoensis ouwens 1912) dengan burung gosong (Megapodius frecinet Gaimard 1823) di Pulau Komodo Taman Nasional Komodo Nusa Tenggara Timur
Abstrak: Komodo (Varanus komodoensis) merupakan salah satu jenis reptilia langka endemik yang hanya menyebar di Pulau Komodo, Rinca, dan Flores (Mulyana, 1994). Beberapa penelitian tentang jenis ini mulai dari perilaku, ekologi, reproduksi bahkan morfologinya masih terus dilakukan (Simanjuntak, et. al. 1993). Adanya penelitian aktifitas harian dan perilaku komodo oleh Mulyana dari bulan Juni sampai Agustus 1992, muncul dugaaan baru bahwa dalam perilaku reproduksinya komodo memanfaatkan. bekas sarang burung gosong (Megapodius freycinet) sebagai tempat bertelurnya. Berdasarkan penelitian tersebut, nampak ada suatu hubungan yang unik antara komodo dengan burung gosong. Tujuan penelitian ini adalah untuk mengetahui bentuk-bentuk interaksi, faktor penyebab interaksi, waktu dan karakteristik tempat interaksi antara komodo dan burung gosong. ...
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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