Open AccessKlasifikasi Teh Hijau dan Teh Hitam Tambi-Pagilaran dengan Metode Principal Component Analysis (PCA) Menggunakan E-Nose
Author(s) -
Inca Inca,
Triyogatama Wahyu Widodo,
Danang Lelono
Publication year - 2018
Publication title -
ijeis (indonesian journal of electronics and instrumentation system)/ijeis (indonesian journal of electronics and instrumentation systems)
Language(s) - English
Resource type - Journals
eISSN - 2460-7681
pISSN - 2088-3714
DOI - 10.22146/ijeis.28718
Subject(s) - principal component analysis , mathematics , black tea , green tea , statistics , chemistry , food science
This research aims to classification of samples of green tea and black tea originated from different planting sites, Tambi and Pagilaran. Samples of green tea and black tea; quality I (BOP), quality II (BP), quality III (Bohea) were each collected from Tambi and Pagilaran to analyze the charasteristic of both sample from both sites. Measurements of tea samples were performed using a dynamic e-nose device based on a MOS gas sensor, with a maximum set point temperature of 40ºC, flushing 300 seconds, collecting 120 seconds, and purging 80 seconds for 10 cycles repeatedly. The resulting sensor response is then processed using the difference method for baseline manipulation. Characteristic of extraction process on the sensor response results is carried out in three methods; relative, fractional change, and integral. Matrix data of the feature extraction results was reduced using the PCA method by mapping the aroma patterns of each sample using 2-PCA components. The PCA reduction results in integral feature extraction showed the largest percentage of cumulative variance in classifying green tea sample data by 97% and black tea by 100%. The large percentage value of cumulative variance indicates PCA can differentiate samples of green tea and black tea from Tambi and Pagilaran well.