Luwak Coffee Classification Using UV-Vis Spectroscopy Data: Comparison of Linear Discriminant Analysis and Support Vector Machine Methods

Diding Suhandy (Department of Agricultural Engineering, Faculty of Agriculture, The University of Lampung, Jl. Prof. Dr. Soemantri Brojonegoro No.1 Bandar Lampung 35145, Lampung, Indonesia)
Meinilwita Yulia (Department of Agricultural Technology, Lampung State Polytechnic, Jalan Soekarno-Hatta No.10, Rajabasa, Bandar Lampung, Lampung Indonesia, 35141)

Aceh International Journal of Science and Technology
Vol 7, No 2 (2018): August 2018

UV-Vis spectroscopy has been used as a promising method for coffee quality evaluation including in authentication of several high-economic coffee types. In this paper, we have compared the abilities of linear discriminant analysis (LDA) and support vector machines classification (SVMC) methods for Luwak coffee classification. UV-Vis spectral data of 50 samples of pure Luwak coffee and 50 samples of pure non-Luwak coffee were acquired using a UV-Vis spectrometer in transmittance mode. The results show that UV-Vis spectroscopy combined with LDA and SVMC was an effective method to classify Luwak and non-Luwak coffee samples. The classification result was acceptable and yielded 100% classification accuracy for both LDA and SVMC methods. However, due to the simplicity and volume of the required calculation, in this present study LDA method is superior to SVMC method.