Comparison of Extracted Haar Wavelet Features for Herbal Leaf Type Classification
Plants are incredibly beneficial to human survival in various ways. Leaves are part of plants widely used as medicine. They are similar in shape but have different advantages. Leaf types can only be identified by experts. This study aims to create a classification system for herbal leaves based on t...
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| Format: | Article |
| Language: | English |
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EDP Sciences
2024-01-01
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| Series: | E3S Web of Conferences |
| Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2024/125/e3sconf_iconard2024_02004.pdf |
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| author | Jusman Yessi Arisandy Kusumaning Putri Arif Nur Nazilah Chamim Anna Ardiyanto Yudhi |
| author_facet | Jusman Yessi Arisandy Kusumaning Putri Arif Nur Nazilah Chamim Anna Ardiyanto Yudhi |
| author_sort | Jusman Yessi |
| collection | DOAJ |
| description | Plants are incredibly beneficial to human survival in various ways. Leaves are part of plants widely used as medicine. They are similar in shape but have different advantages. Leaf types can only be identified by experts. This study aims to create a classification system for herbal leaves based on the Haar wavelet transform and machine learning. The study was carried out to assist ordinary people in recognizing herbal leaves. The results revealed that Haar wavelet level 1 was better suited to the leaf data. The Quadratic SVM model yielded the highest result with an accuracy of 77%, a precision of 83%, a recall of 83%, a specificity of 82%, and an F-score of 73%. |
| format | Article |
| id | doaj-art-b28838bae0af4f3db589a01c68f108bf |
| institution | OA Journals |
| issn | 2267-1242 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | E3S Web of Conferences |
| spelling | doaj-art-b28838bae0af4f3db589a01c68f108bf2025-08-20T02:19:35ZengEDP SciencesE3S Web of Conferences2267-12422024-01-015950200410.1051/e3sconf/202459502004e3sconf_iconard2024_02004Comparison of Extracted Haar Wavelet Features for Herbal Leaf Type ClassificationJusman Yessi0Arisandy Kusumaning Putri Arif1Nur Nazilah Chamim Anna2Ardiyanto Yudhi3Department of Electrical Engineering, Center of Artificial Intelligence and Robotics Studies, Faculty of Engineering, Universitas Muhammadiyah YogyakartaDepartment of Electrical Engineering, Faculty of Engineering, Universitas Muhammadiyah YogyakartaFaculty of Electrical Engineering and Technology, Universiti Malaysia Perlis (UniMAP)Department of Electrical Engineering, Faculty of Engineering, Universitas Muhammadiyah YogyakartaPlants are incredibly beneficial to human survival in various ways. Leaves are part of plants widely used as medicine. They are similar in shape but have different advantages. Leaf types can only be identified by experts. This study aims to create a classification system for herbal leaves based on the Haar wavelet transform and machine learning. The study was carried out to assist ordinary people in recognizing herbal leaves. The results revealed that Haar wavelet level 1 was better suited to the leaf data. The Quadratic SVM model yielded the highest result with an accuracy of 77%, a precision of 83%, a recall of 83%, a specificity of 82%, and an F-score of 73%.https://www.e3s-conferences.org/articles/e3sconf/pdf/2024/125/e3sconf_iconard2024_02004.pdf |
| spellingShingle | Jusman Yessi Arisandy Kusumaning Putri Arif Nur Nazilah Chamim Anna Ardiyanto Yudhi Comparison of Extracted Haar Wavelet Features for Herbal Leaf Type Classification E3S Web of Conferences |
| title | Comparison of Extracted Haar Wavelet Features for Herbal Leaf Type Classification |
| title_full | Comparison of Extracted Haar Wavelet Features for Herbal Leaf Type Classification |
| title_fullStr | Comparison of Extracted Haar Wavelet Features for Herbal Leaf Type Classification |
| title_full_unstemmed | Comparison of Extracted Haar Wavelet Features for Herbal Leaf Type Classification |
| title_short | Comparison of Extracted Haar Wavelet Features for Herbal Leaf Type Classification |
| title_sort | comparison of extracted haar wavelet features for herbal leaf type classification |
| url | https://www.e3s-conferences.org/articles/e3sconf/pdf/2024/125/e3sconf_iconard2024_02004.pdf |
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