Identifikasi Senyawa Metanol Menggunakan Gugusan Sensor Gas Berbasis Semikonduktor Oksida Logam

Anafiesma, Anugerah Putri (2021) Identifikasi Senyawa Metanol Menggunakan Gugusan Sensor Gas Berbasis Semikonduktor Oksida Logam. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Telah dilakukan identifikasi senyawa metanol dengan gugusan sensor gas berbasis semikonduktor oksida logam dengan metode klasterisasi dan klasifikasi yaitu Principal Component Analysis (PCA), K-Means clustering, Agglomerative Clustering dan Decision Tree. Penelitian ini dilakukan dengan menguji gugusan sensor gas dengan uji kualitatif dan kuantitatif. Pada uji kualitatif digunakan senyawa amonia, asam asetat, aseton dan metanol yang dilakukan 10 kali perulangan pada masing-masing senyawa. Sedangkan untuk uji kuantitatif digunakan senyawa metanol yang dicampur dengan aquades dengan 5 macam variasi rasio yaitu 0,2; 0,3; 0,4; 0,5 dan 0,6. Pada uji kualiatif, gugusan sensor gas dapat membedakan keempat senyawa tersebut dengan baik ke dalam 4 klaster dengan metode PCA, K-Means Clustering dan Decision Tree. Pada uji kuantitatif, dilakukan klasterisasi dengan metode PCA, K-Means Clustering dan Agglomerative Clustering. Ketiga metode tersebut berhasil mengklasterisasi data uji kuantitatif ke dalam 5 klaster sesuai dengan jumlah variasi rasio yang diuji.
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The identification of methanol compounds was carried out using gas sensor array based on metal oxide semiconductors using clustering and classification methods, namely Principal Component Analysis (PCA), K-Means Clustering, Agglomerative Clustering and Decision Tree. This research was conducted by testing the gas sensor array with qualitative and quantitative tests. In the qualitative test, ammonia, acetic acid, acetone and methanol compounds were used with 10 replicates for each compound. For the quantitative test, methanol compounds mixed with distilled water with 5 kinds of ratio changes, namely 0.2; 0.3; 0.4; 0.5 and 0.6. In the qualitative test, the gas sensor cluster can distinguish the four compounds well into 4 clusters using the PCA, K-Means Clustering and Decision Tree methods. In the quantitative test, clustering was carried out using the PCA, K-Means Clustering and Agglomerative Clustering methods. The three methods succeeded in grouping the quantitative test data into 5 clusters according to the number of variations in the ratio tested.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Metanol, Gugusan Sensor Gas, Semikonduktor Oksida Logam, Klasterisasi, Klasifikasi, Gas Sensor Array, Metal-Oxide Semiconductor, Clustering, Classification
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:	Anugerah Putri Anafiesma
Date Deposited:	31 Aug 2021 03:16
Last Modified:	31 Aug 2021 03:16
URI:	http://repository.its.ac.id/id/eprint/90636

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