IMPLEMENTASI TRANSFORMASI FOURIER UNTUK TRANSFORMASI DOMAIN WAKTU KE DOMAIN FREKUENSI PADA LUARAN PURWARUPA ALAT PENDETEKSIAN GULA DARAH SECARA NON-INVASIF

Authors

  • Umam Hidayaturrohman Department of Statistics, IPB University, Indonesia
  • Erfiani Erfiani Department of Statistics, IPB University, Indonesia
  • Farit M Afendi Department of Statistics, IPB University, Indonesia

DOI:

https://doi.org/10.29244/ijsa.v4i2.504

Keywords:

DFT, Diabetes Mellitus, FFT Radix-2, FFT Radix-4, Non-Invasive

Abstract

Diabetes mellitus is the result of changes in the body caused by a decrease of insulin performance which is characterized by an increase of blood sugar level. Detection of blood sugar can be done with Invasive methods or non-invasive methods. However, non-invasive methods are considered better because they can check early, faster and accurate. The prototype output is values of intensity in the time domain, thus fourier transformation is very much needed to transform into the frequency domain. In this study, Fourier transformation methods used are Discrete Fourier Transform (DFT), Fast Fourier Transform Radix-2, and Fast Fourier Transform Radix-4. Evaluation for the best method is done by comparing the processing speed of each method. The FFT Radix-4 method is more effective to perform the transformation into the frequency domain. The average processing speed with the FFT Radix-4 method reaches 2.67×105 nanoseconds, and this is much faster 5.06×106 nanoseconds than the FFT Radix-2 method and 2.40×107 nanoseconds faster than the DFT method.

Downloads

Download data is not yet available.

References

Almeida-Trinidad, R., & Garnica-Garza, H. (2007). A study on the application of Fourier series in IMRT treatment planning. Australasian Physics & Engineering Sciences in Medicine, 30(4): 260–268.

Fain, J. A. (2009). Understanding diabetes mellitus and kidney disease. Nephrology Nursing Journal, 36(5): 465–470.

Jaladi, V., & Swamy, K. P. (2015). Implementation and comparison of Radix-2, Radix-4 and Radix-8 FFT algorithm. International Journal of Ethics in Engineering & Management Education, 2(8): 40–44.

Kassahun, C. W., & Mekonen, A. G. (2017). Knowledge, attitude, practices and their associated factors towards diabetes mellitus among non diabetes community members of Bale Zone administrative towns, South East Ethiopia. A cross-sectional study. PloS One, 12(2): e0170040.

Kim, T. (2003). Determination of Frequencies from Fringe Patterns Using Short-time Fourier Transforms and Wavelet Transforms (PhD Thesis). Chicago (US): Illinois Institute of Technology.

Lasijo, R. (2005). Perhitungan Transformasi Fourier Cepat 1-dimensi dengan Radiks Gabungan Em Pat dan Dua Serta Contoh Penggunaannya. Jurnal Sains Dan Teknologi Nuklir Indonesia (Indonesian Journal of Nuclear Science and Technology), 1(2): 99–119.

Li, Y. (1997). Mechanisms for platelet hyperactivity and abnormal calcium homeostasis in dia etes mellitus (Thesis). Winnipeg (CA): University of Manitoba.

Tedjo, A., Prafiantini, E., Suprapto, A. P., Ibrahim, A. S., Riyanto, S. A., & Priyanto, D. (2014). A Simple Photometer as a Helping Device in Measuring Blood Glucose. Makara Journal of Health Research, 18(2): 77–80.

Wintarti, A., & Suprapto, Y. K. (2011). Perbandingan Ketepatan dan Kecepatan pada Algoritma DFT dan FFT. Presented at the Semnastika-Unesa, Matematika Membangun Insan Kritis dan Kreatif, Surabaya (ID): Universitas Negeri Surabaya.

Zhang, J., & Li, Z. (2013). An algorithm for computing the radix-2n fast fourier transform. Sensors and Transducers, 154: 260–265.

Downloads

Published

2020-07-31

How to Cite

Hidayaturrohman, U., Erfiani, E., & Afendi, F. M. (2020). IMPLEMENTASI TRANSFORMASI FOURIER UNTUK TRANSFORMASI DOMAIN WAKTU KE DOMAIN FREKUENSI PADA LUARAN PURWARUPA ALAT PENDETEKSIAN GULA DARAH SECARA NON-INVASIF. Indonesian Journal of Statistics and Its Applications, 4(2), 234–244. https://doi.org/10.29244/ijsa.v4i2.504

Issue

Section

Articles