The study of groundwater source by using KNN classification
This study was focused on assessing the groundwater as a source using odor by electronic nose (E-nose). Water is a finite resource that essential for humans and ecosystem existence. The suitable quality water resources need to be paid attention since it controlled by naturalistic activities such as...
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| Format: | Conference or Workshop Item |
| Language: | English English |
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| Online Access: | http://umpir.ump.edu.my/id/eprint/32766/ http://umpir.ump.edu.my/id/eprint/32766/1/The%20study%20of%20groundwater%20source%20by%20using%20KNN%20classification.pdf http://umpir.ump.edu.my/id/eprint/32766/2/The%20study%20of%20groundwater%20source%20by%20using%20KNN%20classification.pdf |
| _version_ | 1848824104909537280 |
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| author | Suziyanti, Zaib Muhammad Sharfi, Najib Suhaimi, Mohd Daud Muhammad Faruqi, Zahari Mujahid, Mohamad |
| author_facet | Suziyanti, Zaib Muhammad Sharfi, Najib Suhaimi, Mohd Daud Muhammad Faruqi, Zahari Mujahid, Mohamad |
| author_sort | Suziyanti, Zaib |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | This study was focused on assessing the groundwater as a source using odor by electronic nose (E-nose). Water is a finite resource that essential for humans and ecosystem existence. The suitable quality water resources need to be paid attention since it controlled by naturalistic activities such as geology, motion of groundwater, and water-rock interaction. In general, it is tasteless, odorless, and nearly colorless liquid but in other aspect, it also fulfills the need of minerals in human body up to a certain limit. The anthropogenic activities had caused an imbalance of these minerals in water that result in degradation of its quality. The aim of this study to apply an E-nose in classification of water and to identify odor pattern. It consists of sensor array which mimic the olfactory receptor in human nose that ability to sniff volatile odor that usually undetectable by human nose. K-Nearest Neighbor (KNN) is applied in performing the intelligent classification with mean feature data as an input. The finding results shows that the E-nose sensitivity, specificity and accuracy indicates at 100% for Euclidean distance. |
| first_indexed | 2025-11-15T03:07:44Z |
| format | Conference or Workshop Item |
| id | ump-32766 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-15T03:07:44Z |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-327662021-12-07T07:26:21Z http://umpir.ump.edu.my/id/eprint/32766/ The study of groundwater source by using KNN classification Suziyanti, Zaib Muhammad Sharfi, Najib Suhaimi, Mohd Daud Muhammad Faruqi, Zahari Mujahid, Mohamad TK Electrical engineering. Electronics Nuclear engineering TS Manufactures This study was focused on assessing the groundwater as a source using odor by electronic nose (E-nose). Water is a finite resource that essential for humans and ecosystem existence. The suitable quality water resources need to be paid attention since it controlled by naturalistic activities such as geology, motion of groundwater, and water-rock interaction. In general, it is tasteless, odorless, and nearly colorless liquid but in other aspect, it also fulfills the need of minerals in human body up to a certain limit. The anthropogenic activities had caused an imbalance of these minerals in water that result in degradation of its quality. The aim of this study to apply an E-nose in classification of water and to identify odor pattern. It consists of sensor array which mimic the olfactory receptor in human nose that ability to sniff volatile odor that usually undetectable by human nose. K-Nearest Neighbor (KNN) is applied in performing the intelligent classification with mean feature data as an input. The finding results shows that the E-nose sensitivity, specificity and accuracy indicates at 100% for Euclidean distance. Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/32766/1/The%20study%20of%20groundwater%20source%20by%20using%20KNN%20classification.pdf pdf en http://umpir.ump.edu.my/id/eprint/32766/2/The%20study%20of%20groundwater%20source%20by%20using%20KNN%20classification.pdf Suziyanti, Zaib and Muhammad Sharfi, Najib and Suhaimi, Mohd Daud and Muhammad Faruqi, Zahari and Mujahid, Mohamad The study of groundwater source by using KNN classification. In: The 6th International Conference on Electrical, Control and Computer Engineering (InECCE2021) , 23rd August 2021 , Microsoft Teams platform. pp. 1-12.. (Unpublished) (Unpublished) |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering TS Manufactures Suziyanti, Zaib Muhammad Sharfi, Najib Suhaimi, Mohd Daud Muhammad Faruqi, Zahari Mujahid, Mohamad The study of groundwater source by using KNN classification |
| title | The study of groundwater source by using KNN classification |
| title_full | The study of groundwater source by using KNN classification |
| title_fullStr | The study of groundwater source by using KNN classification |
| title_full_unstemmed | The study of groundwater source by using KNN classification |
| title_short | The study of groundwater source by using KNN classification |
| title_sort | study of groundwater source by using knn classification |
| topic | TK Electrical engineering. Electronics Nuclear engineering TS Manufactures |
| url | http://umpir.ump.edu.my/id/eprint/32766/ http://umpir.ump.edu.my/id/eprint/32766/1/The%20study%20of%20groundwater%20source%20by%20using%20KNN%20classification.pdf http://umpir.ump.edu.my/id/eprint/32766/2/The%20study%20of%20groundwater%20source%20by%20using%20KNN%20classification.pdf |