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MEMBANDINGKAN REGRESI 4PL DAN LINIER FIT UNTUK VERIFIKASI HORMON 17β-ESTRADIOL MENGGUNAKAN METODE ELISA Arroofita Ani Sandiya; Sudjarwo; Ashon Sa’adi
Journal of Research and Technology Vol. 5 No. 1 (2019): JRT Volume 5 No 1 Jun 2019
Publisher : 2477 - 6165

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

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.
VERIFIKASI LINIERITAS KURVA BAKU TESTOSTERON MENGGUNAKAN METODE ELISA (ENZYME-LINKED IMMUNOSORBENT ASSAY) Muhammad Arif Hanny Ferry Fernanda; Ashon Sa’adi; Sudjarwo
Journal of Research and Technology Vol. 5 No. 1 (2019): JRT Volume 5 No 1 Jun 2019
Publisher : 2477 - 6165

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Enzyme-Linked Immunosorbent Assay (ELISA) is one of the quantitative analysis methods that is often used to determine the levels of active compounds in biological samples. In this study we will verify the method of determining testosterone active compounds in blood and urine samples of female patients who have Polycystic Ovary Syndrome (PCOS) using the Human Testosterone ELISA Kit. Before conducting testosterone levels using ELISA, it is necessary to verify the linearity of the standard curve first to determine the effect of testosterone standard levels on the analyte response in the form of optical density. The linearity verification of the standard testosterone curve was calculated using linear regression calculations with determinant coefficient result was 0.978 and a value of α = 0.05. While for testing by using 4 parameter logistic (4PL) coefficient created, 0.999. Based on these results it can be concluded that the testosterone standard level has a significant influence on the response of optical density analytes.
Standardization of Myristicin in Nutmeg (Myristica fragrans Houtt.) Fruit using TLC-Densitometric Method Engel, Daniella Elizabeth; Sudjarwo; Sukardiman
JURNAL FARMASI DAN ILMU KEFARMASIAN INDONESIA Vol. 11 No. 1 (2024): JURNAL FARMASI DAN ILMU KEFARMASIAN INDONESIA
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jfiki.v11i12024.12-19

Abstract

Background: Myristica fragrans Houtt. (Myristicaceae family), with the main content of myristicin, has been immensely used in herbal medicine. Standardization is essential to ensure the safety of natural extracts and the quality of herbal medicines using various chemical analysis techniques. Method validation is necessary to ascertain the reliability and reproducibility of the method. Myristicin is a member of the phenylpropene group, a natural organic compound found in small amounts in nutmeg fruit, which has pharmacological effects. Objective: This study aims to determine the myristicin content in nutmeg fruit using TLC-Densitometry. Methods: Determination of myristicin in nutmeg fruit extract was performed using TLC-Densitometry with silica GF254 as stationary phase, mobile phase n-hexane: ethyl acetate (8:2 v/v), and spot visualized at 285 nm. In this study, the content of myristicin in nutmeg fruit was determined using compendial methods (AOAC), thus requiring method verification with parameters including selectivity, linearity, precision, LOD, and LOQ. Results: The validation of this method showed good linearity and selectivity with y = 0.0001x + 0.0226 (r = 0.9996) and 1.53 (>1.5), respectively. The LOD and LOQ results were low with values of 0.11 μg/spot and 0.33 μg/spot, respectively. The percentage coefficient of variation for precision was below the requirement value of not more than 4%. The average myristicin content in nutmeg fruit extract was approximately 0.0017 ± 0.0003% (w/w). Conclusion: The developed method was valid and sensitive for the quantification of myristicin content in nutmeg fruit.
MEMBANDINGKAN REGRESI 4PL DAN LINIER FIT UNTUK VERIFIKASI HORMON 17β-ESTRADIOL MENGGUNAKAN METODE ELISA Arroofita Ani Sandiya; Sudjarwo; Ashon Sa’adi
Journal of Research and Technology Vol. 5 No. 1 (2019): JRT Volume 5 No 1 Jun 2019
Publisher : 2477 - 6165

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55732/jrt.v5i1.445

Abstract

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.
VERIFIKASI LINIERITAS KURVA BAKU TESTOSTERON MENGGUNAKAN METODE ELISA (ENZYME-LINKED IMMUNOSORBENT ASSAY) Muhammad Arif Hanny Ferry Fernanda; Ashon Sa’adi; Sudjarwo
Journal of Research and Technology Vol. 5 No. 1 (2019): JRT Volume 5 No 1 Jun 2019
Publisher : 2477 - 6165

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55732/jrt.v5i1.446

Abstract

Enzyme-Linked Immunosorbent Assay (ELISA) is one of the quantitative analysis methods that is often used to determine the levels of active compounds in biological samples. In this study we will verify the method of determining testosterone active compounds in blood and urine samples of female patients who have Polycystic Ovary Syndrome (PCOS) using the Human Testosterone ELISA Kit. Before conducting testosterone levels using ELISA, it is necessary to verify the linearity of the standard curve first to determine the effect of testosterone standard levels on the analyte response in the form of optical density. The linearity verification of the standard testosterone curve was calculated using linear regression calculations with determinant coefficient result was 0.978 and a value of α = 0.05. While for testing by using 4 parameter logistic (4PL) coefficient created, 0.999. Based on these results it can be concluded that the testosterone standard level has a significant influence on the response of optical density analytes.