RANCANG BANGUN UNSUPERVISED KOHONEN UNTUK PENGOLAHAN DATA HIDUNG ELEKTRONIK; UNSUPERVISED KOHONEN PROTOTYPE FOR ELECTRONIC NOSE DATA PROCESSING

Hendriyan, Andika S, Triyogatama Wahyu Widodo

2015 | Skripsi | FMIPA

Electronic nose has been developed in various industrial fields. For identification’s problem in electronic nose, artificial neural network is used to data analysis. Generally, artificial neural network’s implementation used application program with artificial neural network’s tools in it. But, that tool didn’t explain artificial neural network specifically. Therefore, needed artificial neural network with special function for identification problem. Neural network models or Kohonen SOM has been created using LabVIEW . SOM neural network has been tested with input variations of iterations between 1-50, learning rate between 0.1-0.9, and weight between 0.1-0.5. From this test, has produced teh best output of identification. Tests using tea and tofu. Teh parameter of achievement is such data in accordance with input data. Teh program has also been proven can be used, using samples that have been investigated in previous studies. Based on teh results of tests on samples of tea, teh accuracy of SOM neural network reached 96.66%, So that identification process has to be done using an artificial neural network created in LabVIEW.

Kata Kunci : ANN,; e-nose; LabVIEW; SOM; Kohonen; identification