Rancang Bangun Instrumentasi Elektrokardiograf (EKG) dan Klasifikasi Kenormalan Jantung Pada Pola Sinyal EKG Menggunakan Learning Vector Quantization (LVQ)

Maulana Maulana (1), Hendrick Hendrick (2), Ratna Aisuwarya (3)
(1) Andalas University
(2) Politeknik Negeri Padang
(3) andalas university
Fulltext View | Download
How to cite (IJASEIT) :
Maulana, M., Hendrick, H., & Aisuwarya, R. (2018). Rancang Bangun Instrumentasi Elektrokardiograf (EKG) dan Klasifikasi Kenormalan Jantung Pada Pola Sinyal EKG Menggunakan Learning Vector Quantization (LVQ). JITCE (Journal of Information Technology and Computer Engineering), 2(01), 19–26. https://doi.org/10.25077/jitce.2.01.19-26.2018

Electrocardiograph (ECG) is a recorder of human heart signals with signal output on a monitor or graph paper. The ECG records the measurement of the electrical activity of the heart from the surface of the body by a set of electrodes that are installed in such a way that reflects the tapping point activity. The pattern of ECG output signals in one heartbeat produces a pattern with a peak point P, Q, R, S and T or QRS complex. ECG signal waveform results were analyzed using Learning Vector Quantization (LVQ) Artificial Neural Networks, and grouped into two classes, namely normal and abnormal heart patterns. The normal heart condition that is trained is a medically normal heart categorized as healthy as 10 data, while an abnormal heart (Heart, Coronary Heart, and Aortic Regurgutation) is 20 data. The LVQ method recognizes the input pattern based on the proximity of the two vectors, namely the vector of the input unit or neuron with the weight vector produced by each class. Online LVQ identification (using ECG) recorded from 25 direct trials resulted in 80% accuracy.

1. Basaruddin, T, dkk. 2011. Klasifikasi Beat
Aritmia Pada Siyal EKG Menggunakan Fuzzy

Wavelet Learning Vector Quantization. Universitas Negeri Surabaya, Surabaya.

2. Darmawansyah, dkk. 2006. Pembuatan Elektrokardiograf (EKG) Teknologi Hibrid Menggunakan Komponen Surface Mounting Device (SMD). Jurnal. Universitas Gadjah Mada. Yogyakarta.

3. Fitrian, Nur. 2007. Bab II. Skripsi.
Universitas Sumatera Utara, Medan.

4. Hidayati, Nurul, Budi Warsito. Prediksi Terjangkitnya Penyakit Jantung Dengan Metode Learning Vector Quantization.2010. Universitas Diponegoro, Semarang.

5. http://www.forumsains.com/artikel/94/?print
diakses tanggal 10 September 2013

6. Purnamasari, Rita, dkk. Perhitungan Denyut Jantung Berdasarkan Sinyal EKG Berbasis FPGA. Jurnal. Institut Teknologi Telkom. Bandung.

7. Rahmat. 2009. Perancangan dan Realisasi Elektrokardiograf Menggunakan Jaringan Syaraf Tiruan Untuk Identifikasi Kelainan Jantung. Jurnal. Politeknik Negeri Padang. Padang.

1. License

Creative Commons License

 

The non-commercial use of the article will be governed by the Creative Commons Attribution license as currently displayed on Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License

2. Author(s)’ Warranties

The author(s) warrants that the article is original, written by stated author(s), has not been published before, contains no unlawful statements, does not infringe the rights of others, is subject to copyright that is vested exclusively in the author and free of any third party rights, and that any necessary permissions to quote from other sources have been obtained by the author(s).

3. User Rights

JITCE adopts the spirit of open access and open science, which disseminates articles published as free as possible under the Creative Commons license. JITCE permits users to copy, distribute, display, and perform the work for non-commercial purposes only. Users will also need to attribute authors and JITCE on distributing works in the journal.

4. Rights of Authors

Authors retain the following rights:

  • Copyright, and other proprietary rights relating to the article, such as patent rights,
  • the right to use the substance of the article in future own works, including lectures and books,
  • the right to reproduce the article for own purposes, 
  • the right to self-archive the article.
  • the right to enter into separate, additional contractual arrangements for the non-exclusive distribution of the article's published version (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal (Journal of Information Technology and Computer Engineering).

5. Co-Authorship

If the article was jointly prepared by other authors; upon submitting the article, the author is agreed on this form and warrants that he/she has been authorized by all co-authors on their behalf, and agrees to inform his/her co-authors. JITCE will be freed on any disputes that will occur regarding this issue. 

7. Royalties

By submitting the articles, the authors agreed that no fees are payable from JITCE.

 

8. Miscellaneous

JITCE will publish the article (or have it published) in the journal if the article’s editorial process is successfully completed and JITCE or its sublicensee has become obligated to have the article published. JITCE may adjust the article to a style of punctuation, spelling, capitalization, referencing and usage that it deems appropriate. The author acknowledges that the article may be published so that it will be publicly accessible and such access will be free of charge for the readers. 

Downloads

Download data is not yet available.