Judul: Perkembangan larva ikan betutu, Oxyleotris marmorata (Blkr.)
Abstrak: Percobaan ini bertujuan untuk mengetahui perkembangan larva ikan betutu mulai dari saat menetas sampai mencapai bentuk definitif (bentuk menyerupai induknya). Percobaan dilakukan di Laboratorium Fakultas Perikanan, Institut Pertanian Bogor, Darmaga dari tanggal 8 Juli sampai 4 Agustus 1990. Bahan yang digunakan adalah telur ikan betutu: hasil pemijahan secara semi alami di kolam. Penetasan dilakukan di akuarium sedang pemeliharaan larva di kolam yang dipupuk. Larva yang digunakan adalah yang menetas pada hari ketiga. Pemberian plankton yang lolos saringan 100 dilakukan pada larva umur satu hari sampai 1,5 hari, yaitu: saat larva menjelang ditebar ke kolam pendederan. Penga- matan larva dilakukan secara mikroskopis dan aspek yang diamati meliputi: diameter kuning telur, diameter butir minyak, diameter mata, panjang total, panjang dari mulut ke anus, tinggi bukaan mulut maksimum, tinggi badan, perkembangan sirip, sisik, pigmen, bobot larva, jenis dan jumlah jasad pakan yang terdapat dalam saluran pencernaan: serta persentase larva yang makan.
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Judul: Perkembangan larva ikan betutu Oxyeleotris marmorata (BLKR), yang dipelihara di kolam dan di tangki
Abstrak: Penelitian perkembangan ini bertujuan untuk mengetahui perbedaan perkembangan larva ikan betutu yang dipelihara di kolam dan tangki. Pemeliharaan larva dilakukan didalam hapa berukuran 1x1x0,8 m berukuran yang dibenamkan di kolam beton berukuran 4x2x0,6m yang telah ditumbuhi pakan alami. Penumbuhan pakan alami dengan cara pengeringan selama 2 hari, lalu dipupuk dengan 100g kotoran ayam/2 dan diairi setinggi 20cm. Tiga hari kemudian dilakukan penyemprotan diazinon 60 EC dengan dosis 7mg/1. Jumlah larva yang dipelihara dihapa adalah 14 ekor/1. ..dst
Keyword: Oxyeleotris marmorata, Ikan betutu, Larva ikan, Pakan ikan

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