Linear Discriminant Analysis (LDA) and Partial Least Square (PLS) of chemometric in mixture of lard and palm oil-based on ftir-spectroscopy data

Tazi, Imam (2023) Linear Discriminant Analysis (LDA) and Partial Least Square (PLS) of chemometric in mixture of lard and palm oil-based on ftir-spectroscopy data. Presented at The 12th International Conference on Green Technology (ICGT 2022), 26-27 Oct 2022, Malang, Indonesia.

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Abstract

Oil as a basic food requirement is often misused by irresponsible individuals, such as lard mixed in palm oil. This is certainly detrimental to society. Indonesia which has a majority Muslim population will have a big influence on the authenticity of oil. FTIR can be an alternative way to distinguish authentic and mixed foods or oils. The purpose of this study is to find out the difference between lard, palm oil, and the mixture of both by using FTIR combined with LDA (Linear Discriminant Analysis) and PLS and find out how much the contribution of LDA and PLS in distinguishing mixed pig oil, palm oil and oil both. The results obtained showed that FTIR was less effective in distinguishing between samples so it was necessary to combine it with LDA and PLS. LDA processed with the stepwise method gives good grouping results. There are two discriminant functions obtained. The LDA data shows the first discriminant function that is obtained with a variance value of 99.3% and the second discriminant function with a variance value of 0.07%. The LDA data shows the first discriminant function that is obtained with a variance value of 99.3% and the second discriminant function with a variance value of 0.07%. PLS data shows good results, which can be seen in the R2 value and validation error value (RMSECV) and low calibration error (RMSE).

Item Type:	Conference (Paper)
Keywords:	FTIR; chemometrics; LDA; PLS
Subjects:	02 PHYSICAL SCIENCES > 0299 Other Physical Sciences > 029901 Biological Physics 02 PHYSICAL SCIENCES > 0299 Other Physical Sciences > 029999 Physical Sciences not elsewhere classified
Divisions:	Faculty of Mathematics and Sciences > Department of Physics
Depositing User:	Imam Tazi
Date Deposited:	24 Oct 2023 13:18

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