PENDEKATAN REGRESI POLINOMIAL ORTHOGONAL UNTUK MENENTUKAN KADAR SALINITAS DAN KONSENTRASI LARUTAN KITOSAN PADA PEMBUATAN ANTIBAKTERI

NOVITASARI, HARYANTI (2014) PENDEKATAN REGRESI POLINOMIAL ORTHOGONAL UNTUK MENENTUKAN KADAR SALINITAS DAN KONSENTRASI LARUTAN KITOSAN PADA PEMBUATAN ANTIBAKTERI. Undergraduate thesis, FSM Undip.

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Abstract

Indonesia is one of the countries with big marine resource. It can cause increased marine waste, such as the shells. Shells can be processed into chitosan. Chitosan has the benefits with high economic value, one of the benefit is became a source of natural antibacterial. Antibacterial test of the chitosan and salinity of the S. aureus bactery indicating inhibition zone formation. The larger inhibition zone indicated that antibacterial produced is better. To optimize the level of salinity and concentration of chitosan so this is used polynomial orthogonal regression approach. This approach can be done on design with the quantitative factors and it have same distance. Determination of the degree of polynomial orthogonal based on orthogonal contrasts that have significant factor of salinity and concentration of chitosan, then it can be determined the shape of regression equation. From the that equation can be determined the extreme points using a differential count. When return to the form of the design it can be determined in what levels of salinity and concentration of chitosan that can maximize the inhibition zone in millimeters. After optimization obtained maximum value of salinity is 18,2846375915% and concentration of chitosan is 1,999699328% with assessment of inhibition zone of antibacterial for S. aureus is 1,72486650 mm. Keywords: chitosan, salinity, inhibition zone, quantitative factors, polynomial orthogonal, orthogonal contrast

Item Type:Thesis (Undergraduate)
Subjects:H Social Sciences > HA Statistics
Divisions:Faculty of Science and Mathematics > Department of Statistics
ID Code:43669
Deposited By:INVALID USER
Deposited On:10 Sep 2014 10:37
Last Modified:10 Sep 2014 10:37

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