Pengujian Kemurnian Minyak Kayu Putih Berbasis Electronic Nose Menggunakan  Metode PCA Dan Neural Network

Anwar  Mujadin; Syachrial  Putra Rifaldi; Octarina  Nur Samijayani; Hadi  Suyono; Sukardi; Anang  Lastriyanto

Authors

Anwar Mujadin Universitas Al-Azhar Indonesia, Universitas Brawijaya Malang
Syachrial Putra Rifaldi Universitas Al-Azhar Indonesia
Octarina Nur Samijayani Universitas Al-Azhar Indonesia
Hadi Suyono Universitas Brawijaya Malang
Sukardi Universitas Brawijaya Malang
Anang Lastriyanto Universitas Brawijaya Malang

Keywords:

Electrical Nose (E-Nose), Principal Component Analysis (PCA), Neural Network (NN)

Abstract

Electronic nose (E-Nose) is one of the latest innovations that plays an important role in the identification of aromatic gases besides using gas chromatography-mass spectrometry (GCMS). Qualitative testing of aromatic materials using E-Nose combined with the multivariate principal component analysis (PCA) and neural network (NN) decision tree analysis methods is very necessary at this time. E-Nose in this research was used as a test tool for the concentration (purity) of aromatic gas from eucalyptus essential oil (Melaleuca leucadendron L.) with alcohol impurities. PCA will place the distribution of sample data then map it and group it. A mixture of eucalyptus oil and alcohol obtained PCA1 of 98.58%, while PCA2 had a value of 1.06% with an accumulation of 99.64%. The sample data was then integrated with the NN decision tree model and obtained excellent classification close to 100% while having good-fitting. by not experiencing a gap between training data and testing data. E-Nose requires a stable control system with accurate gas sensors with measurements in the order of milliVolts (mV).

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