Preliminary study on agarwood essential oil and its classification techniques using machine learning
Using essential oils derived from trees for pharmaceutical purposes, incense, aromatherapy, and other areas has expanded its popularity on the international market. However, since human sensory evaluation is still the primary technique used to grade essential oils in Malaysia, the classification tec...
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| Formáid: | Alt |
| Teanga: | English |
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Institute of Advanced Engineering and Science
2023
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| Ábhair: | |
| Rochtain ar líne: | http://umpir.ump.edu.my/id/eprint/38109/1/Preliminary%20study%20on%20agarwood%20essential%20oil.pdf |
| _version_ | 1825815050800070656 |
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| author | Anis Hazirah Izzati Hasnu, Al-Hadi Aqib Fawwaz, Mohd Amidon Siti Mariatul Hazwa, Mohd Huzir Nurlaila, Ismail Zakiah, Mohd Yusoff Saiful Nizam, Tajuddin Mohd Nasir, Taib |
| author_facet | Anis Hazirah Izzati Hasnu, Al-Hadi Aqib Fawwaz, Mohd Amidon Siti Mariatul Hazwa, Mohd Huzir Nurlaila, Ismail Zakiah, Mohd Yusoff Saiful Nizam, Tajuddin Mohd Nasir, Taib |
| author_sort | Anis Hazirah Izzati Hasnu, Al-Hadi |
| collection | UMP |
| description | Using essential oils derived from trees for pharmaceutical purposes, incense, aromatherapy, and other areas has expanded its popularity on the international market. However, since human sensory evaluation is still the primary technique used to grade essential oils in Malaysia, the classification technique for determining their grade is still below standard. Nonetheless, prior studies established new approaches for classifying the grade of essential oils by studying their chemical compounds. Therefore, agarwood essential oil was selected for the suggested model due to the increasing demand and the high cost of the world's natural raw materials. The support vector machine (SVM) using one versus all (OVA) approach was selected as the classifier for agarwood essential oil. This study provides an overview of essential oils and their prior research techniques. In addition, a review of SVM is conducted to demonstrate that the technique is appropriate for future studies. |
| first_indexed | 2024-03-06T13:07:41Z |
| format | Article |
| id | UMPir38109 |
| institution | Universiti Malaysia Pahang |
| language | English |
| last_indexed | 2024-03-06T13:07:41Z |
| publishDate | 2023 |
| publisher | Institute of Advanced Engineering and Science |
| record_format | dspace |
| spelling | UMPir381092023-09-04T06:19:36Z http://umpir.ump.edu.my/id/eprint/38109/ Preliminary study on agarwood essential oil and its classification techniques using machine learning Anis Hazirah Izzati Hasnu, Al-Hadi Aqib Fawwaz, Mohd Amidon Siti Mariatul Hazwa, Mohd Huzir Nurlaila, Ismail Zakiah, Mohd Yusoff Saiful Nizam, Tajuddin Mohd Nasir, Taib HD28 Management. Industrial Management Q Science (General) T Technology (General) Using essential oils derived from trees for pharmaceutical purposes, incense, aromatherapy, and other areas has expanded its popularity on the international market. However, since human sensory evaluation is still the primary technique used to grade essential oils in Malaysia, the classification technique for determining their grade is still below standard. Nonetheless, prior studies established new approaches for classifying the grade of essential oils by studying their chemical compounds. Therefore, agarwood essential oil was selected for the suggested model due to the increasing demand and the high cost of the world's natural raw materials. The support vector machine (SVM) using one versus all (OVA) approach was selected as the classifier for agarwood essential oil. This study provides an overview of essential oils and their prior research techniques. In addition, a review of SVM is conducted to demonstrate that the technique is appropriate for future studies. Institute of Advanced Engineering and Science 2023-02 Article PeerReviewed pdf en cc_by_sa_4 http://umpir.ump.edu.my/id/eprint/38109/1/Preliminary%20study%20on%20agarwood%20essential%20oil.pdf Anis Hazirah Izzati Hasnu, Al-Hadi and Aqib Fawwaz, Mohd Amidon and Siti Mariatul Hazwa, Mohd Huzir and Nurlaila, Ismail and Zakiah, Mohd Yusoff and Saiful Nizam, Tajuddin and Mohd Nasir, Taib (2023) Preliminary study on agarwood essential oil and its classification techniques using machine learning. Indonesian Journal of Electrical Engineering and Computer Science, 29 (2). pp. 753-760. ISSN 2502-4752. (Published) https://doi.org/10.11591/ijeecs.v29.i2.pp753-760 https://doi.org/10.11591/ijeecs.v29.i2.pp753-760 |
| spellingShingle | HD28 Management. Industrial Management Q Science (General) T Technology (General) Anis Hazirah Izzati Hasnu, Al-Hadi Aqib Fawwaz, Mohd Amidon Siti Mariatul Hazwa, Mohd Huzir Nurlaila, Ismail Zakiah, Mohd Yusoff Saiful Nizam, Tajuddin Mohd Nasir, Taib Preliminary study on agarwood essential oil and its classification techniques using machine learning |
| title | Preliminary study on agarwood essential oil and its classification techniques using machine learning |
| title_full | Preliminary study on agarwood essential oil and its classification techniques using machine learning |
| title_fullStr | Preliminary study on agarwood essential oil and its classification techniques using machine learning |
| title_full_unstemmed | Preliminary study on agarwood essential oil and its classification techniques using machine learning |
| title_short | Preliminary study on agarwood essential oil and its classification techniques using machine learning |
| title_sort | preliminary study on agarwood essential oil and its classification techniques using machine learning |
| topic | HD28 Management. Industrial Management Q Science (General) T Technology (General) |
| url | http://umpir.ump.edu.my/id/eprint/38109/1/Preliminary%20study%20on%20agarwood%20essential%20oil.pdf |
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