Comparison Analysis of Data Groupings of Fluctuation Patterns based on the Amplitude Representation Value (ARV)

In this study, we developed an analysis of the data grouping application based on the amplitude representation values (ARV). We use MSCS (multi spectral capacitive sensor) to facilitate the data acquisition process. Furthermore, we compared the 3 objects study in the initial process, such as: H2O, H2O mixed with NaOH and H2O mixed HCl. Here, we apply the quite new method of Tamsir statistical transformation (TST) approach for data processing, which produces 3 fluctuation patterns for each material, namely: MF (Mean Fluctuation), HF (High Fluctuation) and HHF (High High Fluctuation). In the next step, we use the data grouping method at a later stage with the approach of the ARV that are close together at the data processing stage. Hereafter, at the analysis stage, we try to compare the three patterns of fluctuations with several numbers of data sets based on the ARV. Whereas, the results show the value of a small ARV that is found in the 100 data set for each object. While the large ARV value is in the grouping of 200 data set on each object. Hence, we expect this study to be a potential fluctuations reference condition of the material based on the data grouping.