@article{Yulia_Ningtyas_Suhandy_2021, title={Penggunaan UV-Vis Spektroskopi dan Kemometrika untuk Uji Keaslian Kopi Codot Lampung}, volume={26}, url={https://journal.ipb.ac.id/index.php/JIPI/article/view/34218}, DOI={10.18343/jipi.26.4.479}, abstractNote={<p>Codot coffee from Tanggamus, Lampung is one of Indonesian specialty coffee with a very limited production. In this research, an authentication study for the Codot ground roasted coffee was conducted using UV-vis spectroscopy and chemometrics. A total of 330 samples of pure and adulterated Codot coffee was prepared. The adulterated Codot coffee samples were intentionally created by adding a regular coffee (non-Codot coffee) into pure Codot coffee samples with three levels of adulterations: low (10-20%), medium (30-40%), and high level (50-60%). All samples were 0,29 mm in particle size. The extraction procedure was performed with hot distilled water (98°C). The spectral data of coffee samples were acquired using a benchtop UV-visible spectrometer in the range of 190-1100 nm using a transmittance mode. The result showed that the pure and adulterated samples could be discriminated along PC1 and PC2 axis. The classification model was developed using LDA with 90,91% of accuracy could be obtained. The LDA model was used to classify the new samples and resulted in a sensitivity (SEN) of 100%, specificity (SPEC) of 76,67%, precision (PREC) of 78,13%, and accuracy (ACC) of 87,27% could be obtained. Using PLS regression, a PLS model was developed to quantify the percentages of Codot coffee adulteration and resulted in high of coefficient of determination both in calibration and validation (<em>R<sup>2</sup><sub>kal </sub></em>= 0,99 and <em>R<sup>2</sup><sub>val </sub></em>= 0,98). These results showed that UV-vis spectroscopy and chemometrics are suitable for authentication of Codot specialty coffee with RMSEP = 2,68% and RPD in prediction of 6,49.</p> <p>&nbsp;</p> <p>Keywords: authentication, LDA, PCA, PLS regression, UV-vis spectroscopy</p&gt;}, number={4}, journal={Jurnal Ilmu Pertanian Indonesia}, author={Yulia, Meinilwita and NingtyasKurnia Rimadhanti and Suhandy, Diding}, year={2021}, month={Oct.}, pages={479-489} }