Classification of Beef and Lamb Patterns Using Conducting Polymer Sensor Series and Kohonen Algorithm Method

Abstract

Beef and lamb each have a distinctive aroma. Classification of beef and lamb based on the aroma of the meat using an electronic nose. This electronic nose uses a series of sensors consisting of 6 (six) pieces and uses a Conducting Polymer. This polymer has a high resistance so it is widely used as an insulator. However, this resistance has a certain limit where the polymer surface will turn into carbon and conduct electric current if exposed to excessive electric charge. This research was conducted by taking samples of beef and lamb as test samples where these meats were placed in a closed container at room temperature. Data is taken alternately every day to find out the odor of each meat where on the first day data is taken from the odor of beef and on the second day data is taken from the odor of lamb. A two-layer neural network consisting of six input nodes and three output neurons is trained using the Kohonen algorithm with the training process completed in 31 iterations. The test was carried out 20 times for each exposure to steam from the odor of beef and lamb which was carried out alternately. The percentage of success of the system is reaching 90%.