Judul: Kajian National Plant Protection Organization (NPPO) Indonesia: peraturan perundang undangan dan tingkat adopsi international standard/or Phytosanitary Measures (ISPM)
Abstrak: Organisasi perlindungan tumbuhan nasional (National Plant Protection Organization, NPPO) merupakan organisasi perlindungan tumbuhan yang resmi dibentuk oleh pemerintah di setiap negara anggota WTO. Bentuk kelembagaan NPPO setiap negara berbeda-beda, sangat ditentukan oleh perundang-undangan dan bentuk organisasi pemerintahan yang berlaku.
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Judul: Studi tentang departementasi dan pembagian kerja pada beberapa organisasi taman nasional di Indonesia
Abstrak: Sampai tahun 1990, Indonesia telah memiliki 24 unit taman nasional (TN), 10 diantaranya merupakan Unit Pelaksana Teknis (UPT) Taman Nasional Ditjen PHΡΑ. Penunjukan taman nasional sebagai UPT bermaksud untuk meningkatkan intensitas pengelolaannya agar tujuan pengelolaan taman nasional dapat dicapai secara lebih efektif dan efisien. Beberapa peraturan perundangan yang melandasi penyusunan struktur organisasi taman nasional sebagai suatu UPT adalah Surat Keputusan Menteri Kehutanan Nomor 096/Kpts- II/1984 tentang organisasi dan tata kerja taman nasional dan penunjukan wilayah kerjanya didasarkan pada Surat Keputusan Ditjen PHPA Nomor 46/Kpts/VI-Sek/1984 tentang penunjukan wilayah kerja taman nasional. Sehubungan dengan hal tersebut di atas, maka dibutuhkan mekanisme dan tata kerja pengelolaan yang sehat, yang mampu mengatasi segala permasalahan pengelolaan taman nasional…dst
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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