Judul: Habitat perkembangbiakan dan beberapa aspek perilaku Anopheles sundaicus di Kecamatan Padang Cermin Kabupaten Lampung Selatan:
Abstrak: Salah satu penyakit yang masih menjadi masalah kesehatan di Indonesia saat ini adalah malaria, dimana malaria sering menimbulkan kejadian luar biasa (KBL) yang karena banyaknya angka kematian dan kesakitan. walaupun lima tahun etrakhir angka kesakitan akibat malaria cenderung menurun tetapi diperkirakan masih etrdapat 49.6% penduduk Indonesia tinggal di daerah yang beresiko malaria.Lampung Selatan merupakan salah satu kabupaten di Indonesia yang memepunyai angka kesakitan yang cukup tinggi dengan tingkat endemisitas medium case incidence (MCI). Terdapat satu kecamatan yang berstatus high incidence area (HIA) yaitu kecamatan Padang cermin. Letak wilayah Kecamatan Padang Cermin yang ada di pinggir pantai menjadikan temapt ini sebagai tempat tambak oleh sebagian pemiliknya ada yang ditinggalkan sehingga menjadi tempat yang baik untuk berkembangbiakan nyamuk Anopheles.
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Judul: Perilaku Anopheles sundaicus rodenwalt dalam hubungannya dengan penularan penyakit malaria dan cara pemberantasannya di Desa Tarahan, Tanjungan, Lampung Selatan
Abstrak: Tujuan penelitian ini untuk mengetahui puncak aktifitas menggigit nyamuk An sundaicus betina diluar rumah, kebiasaan hinggap didalam rumah pada malam hari, sumber hospes yang disukai, kebiasaan istirahat didalam rumah pada pagi hari dan penyebarannya dalam mencapai sumber darah ..dst
Keyword: Malaria

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