MEMBANDINGKAN REGRESI 4PL DAN LINIER FIT UNTUK VERIFIKASI HORMON 17β-ESTRADIOL MENGGUNAKAN METODE ELISA - Arroofita Ani Sandiya; Sudjarwo; Ashon Sa’adi (2477 - 6165, 2019)
One solution for infertile couples to get offspring is IVF, one of the stages is a HOT procedure. On the stage there is an increasing in steroid hormone levels (estrogen) as a result of ovarian follicles development. The 17β-estradiol hormone was chosen to be verified because it can be used as a marker or marker to show the maturity follicle. Linear and logistic regression are the two most commonly used in curve making models for ELISA sandwich immunoassays. Although linear regression may be useful when analyzing samples included in the linear part of the analyte response curve, logistic regression is the preferred for multiplex immunoassays. Verification of 17β estradiol hormone regression results using linear fit obtained the value of r=0.952 while the regression value used 4PL obtained result r=0.998. But the results shown in the verification of the 17β estradiol hormone good, this were evidenced by using of SPSS software. The value of F obtained was 78.712, where the value was greater than the value of F table (6.61) which means that the value of independent variable (concentration) on value of the dependent variable (optical density value). The linearity values ​​obtained through verification using the 4PL model indicates that the linearity of this method was better based on linear regression.