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Metal Oxides Semiconductor Sensors for Odor Classification

International Journal of Reconfigurable and Embedded Systems (IJRES) · Vol. 6 No. 3 (2017) · pp. 133–149

DOI
10.11591/ijres.v6.i3.pp133-149
ISSN
2722-2608, 2089-4864
Published
2017-11-01
Publisher
Institute of Advanced Engineering and Science
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

The performance of gas sensor will differ and vary due to the surrounding environment changing, the way of implementation, and the position of the sensors to the source. To reach a good result on gas sensors implementation, a performance test on sensors is needed. The results of the tests are useful for characterizing the properties of the particular material or device. This paper discusses the performances of metal oxides semiconductor (MOS) sensors. The sensors are tested to determine the sensors' time response, sensors' peak duration, sensors' sensitivity, and sensors' stability of the sensor when applied to the various sources at different range. Three sources were used in experimental test, namely: ethanol, methanol, and acetone. The gas sensors characteristics are analyzed in open sampling method in order to see the sensors' sensitivity to the uncertainty disturbances, such as wind. The result shows that metal oxides semiconductor sensor was responsive to the 3 sources not only in static but also dynamic conditions. The expected outcome of this study is to predict the MOS sensors' performance when they are applied in robotic implementation. This performance was considered as the training datasets of the sensor for odor classification in this research. From the experiments, It was got, in dynamic experiment, the senrors has average of precision of 93.8-97%, the accuracy 93.3-96.7%, and the recall 93.3-96.7%. This values indicates that the sensors were selective to the odor they sensed.

Collaboration network of the authors

40 authors · 151 co-authorship links · 14 across different organisations · showing the 40 most connected

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Sriwijaya University
  • Politeknik Negeri Sriwijaya
  • Indonesian Institute of Sciences
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Annisa DarmawahyuniSriwijaya University7
Bambang TutukoSriwijaya University6
Ade Iriani SapitriSriwijaya University5
Muhammad Naufal RachmatullahSriwijaya University5
Anggun IslamiSriwijaya University3
Firdaus FirdausAffiliation unknown3
Nyayu Latifah HusniPoliteknik Negeri Sriwijaya3
Akhiar Wista ArumSriwijaya University2
Bhakti Yudho SupraptoSriwijaya University2
Tresna DewiPoliteknik Negeri Sriwijaya1
Pola RismaPoliteknik Negeri Sriwijaya1
Yurni OktarinaPoliteknik Negeri Sriwijaya1
Muhammad RorizPoliteknik Negeri Sriwijaya1
Firdaus FirdausSriwijaya University1
Ghita AthalinaAffiliation unknown1
Muhammad Alpim Alfa RolisAffiliation unknown1
Erliza YuniartiAffiliation unknown1
Radiyati Umi PartanAffiliation unknown1
Hadi SyaputraAffiliation unknown1
Muhammad Taufik RosenoAffiliation unknown1
Sutarno SutarnoIndonesian Institute of Sciences1
Samsuryadi SamsuryadiAffiliation unknown1
Dian Palupi RiniAffiliation unknown1
Renny Amalia PratiwiAffiliation unknown1
Sukemi SukemiAffiliation unknown1
M. Naufal RachmatullahAffiliation unknown1
Ning EliyatiAffiliation unknown1
Yulia RestiAffiliation unknown1
Mau’izatil RahmayaniAffiliation unknown1
Des Alwine ZayantiAffiliation unknown1
Endang Sri KresnawatiAffiliation unknown1
Endro Setyo CahyonoAffiliation unknown1
Nuswil BernolianAffiliation unknown1
Deris StiawanSriwijaya University1
Ahmad ZarkasiAffiliation unknown1
Winda Kurnia SariAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) http://ijres.iaescore.com/index.php/IJRES/oai, first harvested 8 Nov 2026, last seen 8 Nov 2026.
Original metadata (oai_dc)
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	<dc:title xml:lang="en-US">Metal Oxides Semiconductor Sensors for Odor Classification</dc:title>
	<dc:creator>Latifah Husni, Nyayu</dc:creator>
	<dc:creator>Silvia, Ade</dc:creator>
	<dc:creator>Nurmaini, Siti</dc:creator>
	<dc:creator>Yani, Irsyadi</dc:creator>
	<dc:description xml:lang="en-US">The performance of gas sensor will differ and vary due to the surrounding environment changing, the way of implementation, and the position of the sensors to the source. To reach a good result on gas sensors implementation, a performance test on sensors is needed. The results of the tests are useful for characterizing the properties of the particular material or device. This paper discusses the performances of metal oxides semiconductor (MOS) sensors. The sensors are tested to determine the sensors' time response, sensors' peak duration, sensors' sensitivity, and sensors' stability of the sensor when applied to the various sources at different range. Three sources were used in experimental test, namely: ethanol, methanol, and acetone. The gas sensors characteristics are analyzed in open sampling method in order to see the sensors' sensitivity to the uncertainty disturbances, such as wind. The result shows that metal oxides semiconductor sensor was responsive to the 3 sources not only in static but also dynamic conditions. The expected outcome of this study is to predict the MOS sensors' performance when they are applied in robotic implementation. This performance was considered as the training datasets of the sensor for odor classification in this research. From the experiments, It was got, in dynamic experiment, the senrors has average of precision of 93.8-97%, the accuracy 93.3-96.7%, and the recall 93.3-96.7%. This values indicates that the sensors were selective to the odor they sensed.</dc:description>
	<dc:publisher xml:lang="en-US">Institute of Advanced Engineering and Science</dc:publisher>
	<dc:contributor xml:lang="en-US"></dc:contributor>
	<dc:date>2017-11-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:identifier>https://ijres.iaescore.com/index.php/IJRES/article/view/13635</dc:identifier>
	<dc:identifier>10.11591/ijres.v6.i3.pp133-149</dc:identifier>
	<dc:source xml:lang="en-US">International Journal of Reconfigurable and Embedded Systems (IJRES); Vol 6, No 3: November 2017; 133-149</dc:source>
	<dc:source>2722-2608</dc:source>
	<dc:source>2089-4864</dc:source>
	<dc:source>10.11591/ijres.v6.i3</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ijres.iaescore.com/index.php/IJRES/article/view/13635/pdf</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2017 Institute of Advanced Engineering and Science</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>