Identifikasi Senyawa Boraks pada Bakso secara Non Destruktif Menggunakan Spektrum Inframerah Dekat dan Principle Component Analisys

Abstract

The combination of Near Infrared (NIR) Spectroscopy and multivariate analysis using Principle Component Analysis (PCA) was developed to detect the presence of borax in meatballs. The conventional analysis used to detect the presence of borax has been considered inefficient because it is only able to qualify for the presence of borax, but cannot determine the dose of borax used. This study aimed to identify the presence of borax in meatballs using NIR Spectroscopy in the 1000-2500 nm range and maximize PCA performance by combining MSC and SNV pre-treatment with Savitzky Golay second derivative. The results showed that the identification of borax can occur at a wavelength of 1800 - 2500 nm, which is indicated by vibrations at a wavelength of 1865 nm with the atomic structure of C-Cl and the combination of pre-treatment of the second derivative of Savitzky Golay also successful for grouping the data to be better.

Keywords

• borax, meatballs, msc, nir spectroscopy, pca, snv