Principle Component Analysis for Classification of the Quality of Aromatic Rice

14 Sep 2020  ·  Etika Kartikadarma, Sari Wijayanti, Sari Ayu Wulandari, Fauzi Adi Rafrastara ·

This research introduces an instrument for performing quality control on aromatic rice by utilizing feature extraction of Principle Component Analysis (PCA) method. Our proposed system (DNose v0.2) uses the principle of electronic nose or enose. Enose is a detector instrument that work based on classification of the smell, like function of human nose. It has to be trained first for recognizing the smell before work in classification process. The aim of this research is to build an enose system for quality control instrument, especially on aromatic rice. The advantage of this system is easy to operate and not damaging the object of research. In this experiment, ATMega 328 and 6 gas sensors are involved in the electronic module and PCA method is used for classification process.

PDF Abstract


  Add Datasets introduced or used in this paper

Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.