Application of FFT and KNN Methods for the Process of Identifying Sound Signals

Authors

  • Yessi Yunitasari Informatics Engineering Department, Engineering Faculty, PGRI Madiun University
  • Saifulloh Saifulloh Informatics Engineering Department, Engineering Faculty, PGRI Madiun University
  • Daniswara Andhika Putra Harly Informatics Engineering Department, Engineering Faculty, PGRI Madiun University

DOI:

https://doi.org/10.32664/ic-itechs.v5i1.1599

Keywords:

Sound Signals, FFT, KNN, Machine Learning

Abstract

Everyone has a different kind of voice. Sound is a unique thing and has a certain range of frequencies and intensity of sound that can and cannot be heard by humans. we can detect important characteristics of the sound. The Fast Fourier Transform (FFT) algorithm is an algorithm for calculating Discrete Fourier Transform (DFT). Process of Identifying Sound Signals beginning with the sound data was preprocessed, feature extraction using FFT, classification using KNN and finding the nearest distance using the Euclidean distance method, an accuracy result of  79% of the tested data was obtained.

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Published

2024-12-03

Issue

Vol. 5 No. 1 (2024): IC-ITECHS

Section

Articles