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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Indonesian Journal of Electrical Engineering and Computer Science
Andi Setiawan
Universitas Gadjah Mada
Computer Science & IT

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Design of sample display system on electronic nose for synthetic flavor classification Barokah Barokah; Radi Radi; Luthfi Fadillah Zamzami; Andi Setiawan; Joko Purwo Leksono Yuroto Putro
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 2: May 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i2.pp690-698

Abstract

This study aimed to design a controlled sample display system on an electronic nose and test its performance for classifying synthetic flavors. There are four primary components to the electronic nose design. They are a controlled sample display system, detector, signal conditioning and preprocessing, and pattern recognition software. The sample display system consists of six vials. The sample room temperature setpoint is set to 40 ℃. The controlled sample display system has one heater and two fans to even the room temperature. The one-time data collection process consists of flushing (120 s), collecting (180 s), and purging (180 s). The samples for the performance test were synthetic flavors with four different aromas; durian, mocca, orange, and strawberry. Data analysis of gas sensor response was done through two stages; pre-treatment data processing and principal component analysis (PCA). The four samples were clearly different from others, according to the PCA results. The scores of the PC-1, PC-2, and PC-3 cumulative variance were 98.28%.
Performance of electronic nose based on gas sensor-partition column for synthetic flavor classification Radi Radi; Joko Purwo Leksono Yuroto Putro; Muhammad Danu Adhityamurti; Barokah Barokah; Luthfi Fadillah Zamzami; Andi Setiawan
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 20, No 5: October 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v20i5.22358

Abstract

Electronic nose (e-nose) has been developed and implemented in a wide area, included in food industries. This study was conducted to investigate the performance of an e-nose that utilizes a packed gas chromatography column and a gas sensor for classification of synthetic flavor products. There were six aroma variants of synthetic flavor evaluated, namely durian, jackfruit, ambonese banana, melon, orange and lemon. The e-nose was designed with four main parts, namely aroma provider, column and detector room, microcontroller, and data acquisition system. The device was operated automatically at a stable temperature of 60 °C. Collected data consisted of ten data of each sample was preprocessed by baseline equalization and normalization, extracted its distinctive feature and then were analyzed through pattern recognition analysis. There were two kinds of methods used to analyzed the patterns of the data, namely a fuzzy c-means clustering and an artificial neural network (ANN). With the fuzzy c-means clustering, the result was six data clusters with an unbalanced number of members, indicated that this analysis could not classify samples properly. Meanwhile, analysis with the ANN could classify properly the samples with the level of accuracy of 70%.
Co-Authors Barokah Barokah Joko Purwo Leksono Yuroto Putro Luthfi Fadillah Zamzami Muhammad Danu Adhityamurti Radi Radi