Identifikasi Amonia Dengan Gugusan Sensor Gas

Devian, Gabriel Denis (2021) Identifikasi Amonia Dengan Gugusan Sensor Gas. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Gas amonia dikenal sebagai gas yang mudah terbakar dengan bau menyengat namun tidak berwarna dan banyak dijumpai pada atmosfer. Paparan dosis tinggi melebihi ambang batas memiliki dampak negatif baik bagi kesehatan maupun lingkungan dan ekosistem. Oleh karena itu, penelitian dilakukan untuk mendeteksi keberadaan gas amonia menggunakan gugusan sensor gas pada dua jenis pengujian, yakni secara kualitatif dan kuantitatif. Gugusan sensor gas yang digunakan yakni sensor MQ-3, MQ-4, MQ-6, dan MQ-8. Pada uji kualitatif, penelitian dilakukan dengan menginjeksikan amonia, aseton, etanol, dan asam asetat dalam chamber gugusan sensor gas sebanyak 100 μL pada 10 kali perulangan. Analisis data dengan Diagram Scatter Pairplot, PCA, dan K-Means Clustering menunjukkan bahwa gugusan sensor gas dapat membedakan amonia dari senyawa uji lainnya. Metode kuantitatif dilakukan dengan menginjeksikan amonia pada empat variasi rasio dengan aquades, yakni 25%, 50%, 75%, dan 100% sebanyak 100 μL pada 5 kali perulangan. Visualisasi regresi dilakukan dengan Seaborn Regplot dan Radar Plot, dimana salah satu sensor menunjukkan bahwa besarnya sinyal berbanding lurus dengan rasio amonia yang diinjeksikan. Metode klasifikasi berupa Decision Tree Classifier dan klasterisasi berupa PCA, K-Means Clustering, dan Agglomerative Clustering menunjukkan bahwa gugusan sensor dapat memisahkan amonia berdasarkan variasi rasio dengan cukup baik.
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Ammonia gas was known as a flammable gas with a pungent odor but colorless and can be found in the atmosphere. High dose exposure of ammonia has negative impacts on health, environment and ecosystems. Therefore, research to detects ammonia using gas sensor array in two types of testing: qualitatively and quantitatively, was carried out. The gas sensor array used were MQ-3, MQ-4, MQ-6, and MQ-8 sensors. In the qualitative test, the research was carried out by injecting 100 μL of ammonia, acetone, ethanol and acetic acid in a container with gas sensor array with 10 replications. Clustering analysis such as PCA and K-Means Clustering, shows that gas sensor array can distinguish ammonia from the other test compounds. The quantitative analysis was done by injecting ammonia in four different ratios with distilled water, there are 25%, 50%, 75%, and 100% as much as 100 μL with 5 replications. Regression of the sensor signals shows that the signal magnitude was directly proportional to the ratio of injected ammonia. Decision Tree Classifier, PCA, K-Means Clustering, and Agglomerative Clustering show that the sensor array can detect the ammonia based on their ratio quite well.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Gas Sensor Array, Ammonia, Clustering, Classification, Gugusan Sensor Gas, Amonia, Klasterisasi, Klasifikasi
Subjects:	Q Science > QD Chemistry > QD115 Electrochemical analysis Q Science > QD Chemistry > QD75.2 Chemistry, Analytic
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Chemistry > 47201-(S1) Undergraduate Thesis
Depositing User:	Gabriel Denis Devian
Date Deposited:	05 Aug 2021 01:57
Last Modified:	05 Aug 2021 01:57
URI:	http://repository.its.ac.id/id/eprint/84871

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