Author:
Melinda Melinda,Sianturi Patar,Tamsir Agus Santoso
Abstract
Abstract
Multi spectral capacitive sensor (MSCS) is a sensor that is formed based on the concept of white noise impedance spectroscopy. This concept utilizes the spectral noise frequency approach of the frequency domain signal resulting from the field effect on the dielectric. As a sensor, the consistency results obtained is stable, so that it can facilitate analysis. In this study, we tried to compare data groups, starting with 100 data sets and 300 data sets from a total of 600 data sets for H2O and H2O mixed with NaOH materials and H2O mixed with HCl using a new transformation, namely Tamsir statistical transformation (TST). Furthermore, grouping data uses the total amplitude value of each data set obtained. We obtain the results in the form of differences between groups of data with fluctuations in response patterns that are close together which are shown in 2D graphics. Hence, we can implement the data groups as a reference pattern of fluctuations in a material.
Cited by
2 articles.
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1. Application of Convolutional Neural Network (CNN) Method in Fluctuations Pattern;Green Intelligent Systems and Applications;2023-08-08
2. A Novel Subtraction Method for Signal Fluctuation;2022 5th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI);2022-12-08