MEMBANDINGAKAN REGRESI 4 PL DAN LINIER FIT UNTUK VERIFIKASI HORMON 17β-ESTRADIOL MENGGUNAKAN METODE ELISA - Sandiya, Arroofita Ani; Sa'adi, Ashon; Sudjarwo, Sudjarwo (Universitas Nahdlatul Ulama Sidoarjo, 2019)
One solution for infertile couples to get offspring is IVF, where one of the stages is a HOT procedure, at which stage there is an increase in steroid hormone levels (estrogen) as a result of the development of ovarian follicles. The 17β-estradiol hormone was chosen to be verified because it can be used as a marker or marker to show the maturity of the follicle. Linear and logistic regression are the two most commonly used in curve making models for 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 type of regression for multiplex immunoassays. Verification of the 17β estradiol hormone regression results using linear fit obtained the result of r = 0.952 while the regression value used 4 PL to get the result r = 0.998. But the results shown in the verification of the 17β estradiol hormone are good, this is evidenced by the use of SPSS software where F = 78.712 is obtained, where the value is greater than the value of F table (6.61) which means 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 indicate that the method is better linearity reported based on Linear regression.