ELECTRONIC NOSE (E-NOSE) DESIGN FOR ARDUINO NANO-BASED HALAL HARAM IDENTIFICATION
It has been successfully designed an Electronic Nose (e-Nose) instrumentation system consisting of 6 MQ gas sensors, namely, MQ2, MQ4, MQ5, MQ7, MQ9, MQ135. The E-nose system is used to identify halal-haram food. This E-Nose system uses an Arduino Nano microcontroller. The Graphic User Interface (GU...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Jurusan Fisika Fakultas Sains Dan Teknologi, Universitas Islam Negeri Maulana Malik Ibrahim Malang
2021-02-01
|
| Series: | Jurnal Neutrino: Jurnal Fisika dan Aplikasinya |
| Subjects: | |
| Online Access: | https://ejournal.uin-malang.ac.id/index.php/NEUTRINO/article/view/8903 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849235914240294912 |
|---|---|
| author | Muammar Kadafi Rachmad Almi Putra |
| author_facet | Muammar Kadafi Rachmad Almi Putra |
| author_sort | Muammar Kadafi |
| collection | DOAJ |
| description | It has been successfully designed an Electronic Nose (e-Nose) instrumentation system consisting of 6 MQ gas sensors, namely, MQ2, MQ4, MQ5, MQ7, MQ9, MQ135. The E-nose system is used to identify halal-haram food. This E-Nose system uses an Arduino Nano microcontroller. The Graphic User Interface (GUI) system is built with Visual Studio 2008. Then, the data responses will be evaluated by using 2 patterns recognition methods called Principle Component Analysis (PCA). The classification results can be explained by the value of the score plot on the PCA of the data. PC1 accounts for 19% of the variance, and PC2 accounts for 5% of the variance, data obtained is stored and displayed on personal computers in Excel format. Each sample was tested for up to ten repetitions. The data obtained from the six sensors in the e-nose was processed using Minitab 18 and it was necessary to obtain classification data on lard, pig oil, and sample B, which were fried crackers using pork oil. |
| format | Article |
| id | doaj-art-3ea9330a2ea5446f969c3d84b9268fa0 |
| institution | Kabale University |
| issn | 1979-6374 2460-5999 |
| language | English |
| publishDate | 2021-02-01 |
| publisher | Jurusan Fisika Fakultas Sains Dan Teknologi, Universitas Islam Negeri Maulana Malik Ibrahim Malang |
| record_format | Article |
| series | Jurnal Neutrino: Jurnal Fisika dan Aplikasinya |
| spelling | doaj-art-3ea9330a2ea5446f969c3d84b9268fa02025-08-20T04:02:32ZengJurusan Fisika Fakultas Sains Dan Teknologi, Universitas Islam Negeri Maulana Malik Ibrahim MalangJurnal Neutrino: Jurnal Fisika dan Aplikasinya1979-63742460-59992021-02-0113181210.18860/neu.v13i1.89035463ELECTRONIC NOSE (E-NOSE) DESIGN FOR ARDUINO NANO-BASED HALAL HARAM IDENTIFICATIONMuammar Kadafi0Rachmad Almi Putra1Department of Physics, Samudra University Jl. Meurandeh Langsa Aceh 24416, IndonesiaDepartment of Physics, Samudra University Jl. Meurandeh Langsa Aceh 24416, IndonesiaIt has been successfully designed an Electronic Nose (e-Nose) instrumentation system consisting of 6 MQ gas sensors, namely, MQ2, MQ4, MQ5, MQ7, MQ9, MQ135. The E-nose system is used to identify halal-haram food. This E-Nose system uses an Arduino Nano microcontroller. The Graphic User Interface (GUI) system is built with Visual Studio 2008. Then, the data responses will be evaluated by using 2 patterns recognition methods called Principle Component Analysis (PCA). The classification results can be explained by the value of the score plot on the PCA of the data. PC1 accounts for 19% of the variance, and PC2 accounts for 5% of the variance, data obtained is stored and displayed on personal computers in Excel format. Each sample was tested for up to ten repetitions. The data obtained from the six sensors in the e-nose was processed using Minitab 18 and it was necessary to obtain classification data on lard, pig oil, and sample B, which were fried crackers using pork oil.https://ejournal.uin-malang.ac.id/index.php/NEUTRINO/article/view/8903halalharame-nosearduinonano |
| spellingShingle | Muammar Kadafi Rachmad Almi Putra ELECTRONIC NOSE (E-NOSE) DESIGN FOR ARDUINO NANO-BASED HALAL HARAM IDENTIFICATION Jurnal Neutrino: Jurnal Fisika dan Aplikasinya halal haram e-nose arduino nano |
| title | ELECTRONIC NOSE (E-NOSE) DESIGN FOR ARDUINO NANO-BASED HALAL HARAM IDENTIFICATION |
| title_full | ELECTRONIC NOSE (E-NOSE) DESIGN FOR ARDUINO NANO-BASED HALAL HARAM IDENTIFICATION |
| title_fullStr | ELECTRONIC NOSE (E-NOSE) DESIGN FOR ARDUINO NANO-BASED HALAL HARAM IDENTIFICATION |
| title_full_unstemmed | ELECTRONIC NOSE (E-NOSE) DESIGN FOR ARDUINO NANO-BASED HALAL HARAM IDENTIFICATION |
| title_short | ELECTRONIC NOSE (E-NOSE) DESIGN FOR ARDUINO NANO-BASED HALAL HARAM IDENTIFICATION |
| title_sort | electronic nose e nose design for arduino nano based halal haram identification |
| topic | halal haram e-nose arduino nano |
| url | https://ejournal.uin-malang.ac.id/index.php/NEUTRINO/article/view/8903 |
| work_keys_str_mv | AT muammarkadafi electronicnoseenosedesignforarduinonanobasedhalalharamidentification AT rachmadalmiputra electronicnoseenosedesignforarduinonanobasedhalalharamidentification |