Machine learning-based characteristic identification of MSG content in gravy foods
Monosodium Glutamate (MSG) is a sodium salt that binds to amino acids in the form of glutamic acid, widely used as an additive in cooking as a flavoring. Therefore, this research aims to detect the level of MSG content in soupy foods using Machine Learning. This research determines the identificatio...
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| Format: | Article |
| Language: | English |
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EDP Sciences
2024-01-01
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| Series: | BIO Web of Conferences |
| Online Access: | https://www.bio-conferences.org/articles/bioconf/pdf/2024/67/bioconf_icobeaf2024_04019.pdf |
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| author | Rosyady Phisca Aditya Habibah Nurina Umy Masita Yudhana Anton |
| author_facet | Rosyady Phisca Aditya Habibah Nurina Umy Masita Yudhana Anton |
| author_sort | Rosyady Phisca Aditya |
| collection | DOAJ |
| description | Monosodium Glutamate (MSG) is a sodium salt that binds to amino acids in the form of glutamic acid, widely used as an additive in cooking as a flavoring. Therefore, this research aims to detect the level of MSG content in soupy foods using Machine Learning. This research determines the identification of MSG using the Machine Learning method Naive Bayes classifier algorithm in Python software. This tool determines the identification of MSG dissolved in water using a Photodioda sensor, push button, RGB LED, Arduino Nano and Resistor. From the research obtained the results that the color of the light source affects the sensor reading value. Sensor value readings based on different light sources have the same pattern, but different values. The difference in sensor value is caused by the effect of LED color on specimen color. The more MSG used, the greater the photodiode sensor reading value. Based on this research, the accuracy value is 83.6%. |
| format | Article |
| id | doaj-art-de94e64fdd404648bc7e66d2e1bda225 |
| institution | Kabale University |
| issn | 2117-4458 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | BIO Web of Conferences |
| spelling | doaj-art-de94e64fdd404648bc7e66d2e1bda2252025-01-16T11:19:46ZengEDP SciencesBIO Web of Conferences2117-44582024-01-011480401910.1051/bioconf/202414804019bioconf_icobeaf2024_04019Machine learning-based characteristic identification of MSG content in gravy foodsRosyady Phisca Aditya0Habibah Nurina Umy1Masita2Yudhana Anton3Department of Electrical Engineering, Universitas Ahmad Dahlan, BantulDepartment of Health Nutrition, Universitas Gadjah MadaDepartment of Electrical Engineering, Universitas Ahmad Dahlan, BantulDepartment of Electrical Engineering, Universitas Ahmad Dahlan, BantulMonosodium Glutamate (MSG) is a sodium salt that binds to amino acids in the form of glutamic acid, widely used as an additive in cooking as a flavoring. Therefore, this research aims to detect the level of MSG content in soupy foods using Machine Learning. This research determines the identification of MSG using the Machine Learning method Naive Bayes classifier algorithm in Python software. This tool determines the identification of MSG dissolved in water using a Photodioda sensor, push button, RGB LED, Arduino Nano and Resistor. From the research obtained the results that the color of the light source affects the sensor reading value. Sensor value readings based on different light sources have the same pattern, but different values. The difference in sensor value is caused by the effect of LED color on specimen color. The more MSG used, the greater the photodiode sensor reading value. Based on this research, the accuracy value is 83.6%.https://www.bio-conferences.org/articles/bioconf/pdf/2024/67/bioconf_icobeaf2024_04019.pdf |
| spellingShingle | Rosyady Phisca Aditya Habibah Nurina Umy Masita Yudhana Anton Machine learning-based characteristic identification of MSG content in gravy foods BIO Web of Conferences |
| title | Machine learning-based characteristic identification of MSG content in gravy foods |
| title_full | Machine learning-based characteristic identification of MSG content in gravy foods |
| title_fullStr | Machine learning-based characteristic identification of MSG content in gravy foods |
| title_full_unstemmed | Machine learning-based characteristic identification of MSG content in gravy foods |
| title_short | Machine learning-based characteristic identification of MSG content in gravy foods |
| title_sort | machine learning based characteristic identification of msg content in gravy foods |
| url | https://www.bio-conferences.org/articles/bioconf/pdf/2024/67/bioconf_icobeaf2024_04019.pdf |
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