The use of Electronic Nose in Machine Learning-Based of Jengkol (Archidendron Pauchiflorum) Andkabauseeds (Archidendron Bubalinum) Authentication

Dian Mustika - Departement of physics, Universitas Negeri Padang, Jl. Prof. Dr. Hamka Air Tawar Padang 25131
Yenni Darvina - Departement of physics, Universitas Negeri Padang, Jl. Prof. Dr. Hamka Air Tawar Padang 25131
- Yulkifli - Departement of physics, Universitas Negeri Padang, Jl. Prof. Dr. Hamka Air Tawar Padang 25131
Kuwat Triyana - Departement of physics, Gadjah Mada University

Abstract


This research is based on the fact that this difference in economic value can create a potential motive for counterffeiting, although to date there has been no concrete evidence that counterfeiting between these two types of seeds has occurred. Basically, however, jengkol and kabau are also quite similar physically, especially when they are chopped, making it difficult to distinguish them visually even though they have different odors. The sample preparation tools used are digital scales and knives. While the data collection tools used are electronic nose, personal computer, data logger, usb, drain pump, teflon hose, 100 ml beaker, and acrylic box. The materials used are jengkol and kabau seeds.The method used is experimental, where jengkol and kabau are put into a glass beaker which will be tested using an enose connected using a teflon hose and the output results are seen in the data logger.The model used is support vector machine. The performance of the external test data on the SVM model with RBF kernel can be seen in Figure 9. It can be seen that out of 200 data, there are 2 data that are misclassified. Where from the confution matrices, the accuracy is 99.00, Recall_0 is 99.00, and Recall_1 is 99.00. This shows that the model that has been developed remains stable despite changes in the retrieval method and by being carried out in different weeks.

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DOI: http://dx.doi.org/10.24036/16783171074