Judul: Profil Kimia dan Aktivitas Formula Jamu Antidiabetes Berbasis Sambiloto pada Tikus Sprague-Dawley yang Diinduksi Streptozotosin
Abstrak: Formula jamu antidiabetes berbasis sambiloto (Andrographis paniculata) telah diprediksi menggunakan sistem pendekatan yang dikenal dengan SI-IJAH (Sistem Informasi Jamu Herbal Indonesia). Tujuan penelitian ini adalah menentukan profil kimia, toksisitas, dan aktivitas formula jamu pada tikus diabetes yang diinduksi streptozotosin. Simplisia diekstraksi menggunakan pelarut etanol 70%, profil kimia menggunakan Kromatografi Lapis Tipis (KLT), toksisitasnya dengan metode Brine Shrimp Lethality Test (BSLT), dan efektifitas jamu antidiabetes yang diujikan secara in vivo pada tikus dewasa jantan Sprague-Dawley secara oral selama 28 hari. Hasil penelitian menunjukkan pemrofilan menggunakan KLT menghasilkan 11 pita yang terpisah. Toksisitas pada jamu terkategori toksik sedang. Formula jamu antidiabetes dengan konsentrasi sambiloto 5 mg/kgBB dan 10 mg/kgBB, tidak menunjukkan efikasi sebagai penurun gula darah pada tikus diabetes induksi streptozotosin. Penelitian mengekplorasi dosis formula yang efektif masih perlu dilakukan dan perlunya pendekatan metabolomik.
Keyword: BSLT, formula jamu antidiabetes, KLT, toksisitas

Judul: In vivo anti-diabetic assay of jamu formula and its chromatographic fingerprint analysis
Abstrak: Pengujian in vivo khasiat suatu formula jamu penting dilakukan sebelum dikonsumsi oleh manusia. Tujuan penelitian ini adalah membuktikan khasiat antidiabetes dari formula jamu biofarmaka secara in vivo dan menentukan profil sidik jari formula tersebut dengan analisis kromatografi. Uji in vivo menggunakan mencit yang diinduksi diabetes dengan streptozotosin. Efektivitas formula jamu dalam menurunkan kadar gula darah mencit dibandingkan dengan kontrol positif metformin. Berikutnya, metode kromatografi lapis tipis (KLT) dan kromatografi cair kinerja tinggi (KCKT) digunakan untuk menghasilkan profil sidik jari formula jamu. Hasil penelitian menunjukkan bahwa formula jamu biofarmaka dapat menurunkan kadar gula darah mencit diabetes selama perlakuan. Hasil penurunan ini tidak berbeda nyata dengan kontrol positif. Kromatogram KLT formula jamu yang dielusi dengan toluena:aseton:asam asetat menunjukkan 5 pita yang terpisah dengan baik. Adapun analisis KCKT dengan elusi gradien fase terbalik dan fase gerak air:asetonitril dapat menghasilkan pola kromatogram yang dapat berfungsi sebagai sidik jari formula jamu. Kata kunci: analisis sidik jari, jamu antidiabetes, metformin, streptozotosin, In vivo assay of a jamu formula's efficacy is necessary before it is consumed by human. The aims of this study were proving the efficacy of biopharmaca antidiabetic jamu formula by in vivo assay and determine the formula fingerprint profiles with chromatographic analysis. In vivo assay was done using mice which were diabetic-induced by streptozotocin. The effectiveness of jamu formulas in reducing the mice blood sugar level was compared with metformin as a positive control. The fingerprint profiles of jamu formula were further generated by thin layer chromatography (TLC) and high performance liquid chromatography (HPLC) methods. The results showed that the formula of biopharmaca jamu could reduce the blood sugar levels during treatment. The result of this reduction was not significantly different to that of the positive control. TLC chromatogram jamu formula eluted using toluene:acetone:acetic acid showed 5 well-separated spots. The HPLC analysis with phase-reversed gradient elution and mobile phase of water:acetonitrile gave the chromatogram patterns which can serve as fingerprints of jamu formulas. Keywords: anti-diabetic jamu, fingerprint analysis, metformin, streptozotocin
Keyword: analisis sidik jari, jamu antidiabetes, metformin, streptozotosin

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