TY - GEN
T1 - Analysis of consistence level using new method of statistical transformation approach in multi-spectral fluctuation pattern
AU - Melinda,
AU - Tamsir, Agus Santoso
AU - Basari, null
AU - Gunawan, Dadang
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/4/5
Y1 - 2017/4/5
N2 - In this study, quite new method of statistical approach which is known as TST (tamsir statistical transformation) is introduced. TST is applied in order to obtain a consistence level of multi-spectral fluctuation pattern of HHF (high high-frequency). This is done because the data from the measurement results have large amount of data and have not been consistent yet. Therefore, it is essential to have quite good method to treat the data that can bridge the data processing previously. There are several parameters of the data analysis, which will be discussed, such as: The value of Total-C (total value comparison), consistence of fluctuation (CF), consistence of variance to mean ratio (C-VMR) and consistence of value (CV). Besides, the data are broken down into several groups of data. This is done because it is fruitful to seek the best group that has preferable consistence compare to others. The results obtained show that the statistical approach can determine the consistent results of data grouping for large data size. Moreover, the new approach of TST can accommodate to compute the consistence level of multi-spectral fluctuation pattern.
AB - In this study, quite new method of statistical approach which is known as TST (tamsir statistical transformation) is introduced. TST is applied in order to obtain a consistence level of multi-spectral fluctuation pattern of HHF (high high-frequency). This is done because the data from the measurement results have large amount of data and have not been consistent yet. Therefore, it is essential to have quite good method to treat the data that can bridge the data processing previously. There are several parameters of the data analysis, which will be discussed, such as: The value of Total-C (total value comparison), consistence of fluctuation (CF), consistence of variance to mean ratio (C-VMR) and consistence of value (CV). Besides, the data are broken down into several groups of data. This is done because it is fruitful to seek the best group that has preferable consistence compare to others. The results obtained show that the statistical approach can determine the consistent results of data grouping for large data size. Moreover, the new approach of TST can accommodate to compute the consistence level of multi-spectral fluctuation pattern.
KW - consistence level
KW - fluctuation
KW - statistical approach
UR - http://www.scopus.com/inward/record.url?scp=85018978105&partnerID=8YFLogxK
U2 - 10.1109/ICCSCE.2016.7893580
DO - 10.1109/ICCSCE.2016.7893580
M3 - Conference contribution
AN - SCOPUS:85018978105
T3 - Proceedings - 6th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2016
SP - 251
EP - 255
BT - Proceedings - 6th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2016
Y2 - 25 November 2016 through 27 November 2016
ER -