Agarwood Classification using the Electronic Nose Method

Fahreza Haqqi*, Muhammad Rivai, Totok Mujiono

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Agarwood is an important commodity in the perfume industry, and its price depends on its aroma. The resin content is the main factor in the appearance of the distinctive aroma. The differences in agarwood aroma are difficult for human senses to distinguish. In this study, we developed an innovative agarwood aroma classification system using the electronic nose method. This system used a semiconductor gas sensor array to detect and measure the gas emitted by agarwood and a machine learning algorithm for automatic classification purposes. The results of the experiments show that the gas sensor array can provide specific patterns for each type of agarwood, namely Merauke, Bintuni, Sulawesi, and Borneo. The support vector machine (SVM) algorithm can differentiate each type of agarwood with an accuracy of 93.7%.

Original languageEnglish
Title of host publication2024 International Seminar on Intelligent Technology and Its Applications
Subtitle of host publicationCollaborative Innovation: A Bridging from Academia to Industry towards Sustainable Strategic Partnership, ISITIA 2024 - Proceeding
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages396-400
Number of pages5
Edition2024
ISBN (Electronic)9798350378573
DOIs
Publication statusPublished - 2024
Externally publishedYes
Event25th International Seminar on Intelligent Technology and Its Applications, ISITIA 2024 - Hybrid, Mataram, Indonesia
Duration: 10 Jul 202412 Jul 2024

Conference

Conference25th International Seminar on Intelligent Technology and Its Applications, ISITIA 2024
Country/TerritoryIndonesia
CityHybrid, Mataram
Period10/07/2412/07/24

Keywords

  • agarwood
  • electronic nose
  • gas sensors
  • innovation
  • machine learning

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