Self comparison performance analysis of H2O on multi spectral fluctuation pattern

This study aims to obtain the performance of a measured material (H2O) in a multi spectral fluctuation pattern by applying self-comparison method approach. This is done because the data obtained is quite large and also fluctuated. The fluctuation pattern used is HF (high fluctuation) and HHF (high high fluctuation). We propose several stages to exhibit the performance of this fluctuation design. It is started by forming of the data grouping stages that is useful for grouping each range of data. Then, we apply the coding of data set to provide the identity of data. Lastly, self comparison stage is able to analyze the fluctuation pattern activity in the data set obtained. Consequently, we divide this method into two parts, namely: ISC (inner self comparison) and OSC (outer self comparison). Furthermore, we analyze the data by comparing the two methods to the available sub of data sets. So it will indicate which of the sub data sets that have the expected standard values. Besides, there is 2D (dimension) graphics that represent the ISC result for each group. While, for the OSC result, there will be the comparison value to determine among the groups. Thus, we have found that the results obtained from the application of this method are the value of the amplitude percentage ratio that is approximately of 100% for grouping of 200 data sets.