Komputasi Paralel untuk Mendeteksi Gelombang QRS Complex Menggunakan YOLO Deep Learning

Authors

  • Muhammad Achsan Hujjatul Islam Dept. Teknik Komputer Institut Teknologi Sepuluh Nopember Surabaya, Indonesia
  • Muhtadin Dept. Teknik Komputer Institut Teknologi Sepuluh Nopember Surabaya, Indonesia

DOI:

https://doi.org/10.59378/jcenim.v2i3.62

Keywords:

Aritmia, EKG, Komputasi Paralel

Abstract

Penyakit jantung merupakan salah satu penyebab kematian terbesar di dunia. Berdasarkan Riset Kesehatan Dasar (Riskesdas) Kementerian Kesehatan, pada tahun 2018 prevalensi penyakit jantung di Indonesia mencapai 1,5 dari jumlah seluruh penduduk. Salah satu penyebab munculnya penyakit jantung dapat diketahui melalui kondisi ritme jantung. Aritmia merupakan suatu kelainan ritme jantung yang tidak beraturan, terlalu cepat atau terlalu lambat. Kelainan aritmia dapat dideteksi menggunakan Elektrokardiogram (EKG). Deteksi aritmia dengan menggunakan teknologi pada bidang machine learning sangat diperlukan, sehingga dapat mendeteksi dan dilakukan terapi/pengobatan aritmia sedini mungkin untuk mengurangi resiko. Saat ini telah berkembang cara pembacaan dalam rangka panjang dikenal Long Term EKG. Pembacaan ini menghasilkan banyak data, yang tentunya membutuhkan waktu yang lama dalam pengolahannya. Berdasarkan hal tersebut, maka dimanfaatkanlah teknologi komputasi paralel yaitu pemrosesan komputasi secara bersamaan dengan memaksimalkan sumber daya perangkat yang dimiliki sehingga dapat mempersingkat waktu yang dibutuhkan.

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Published

2026-02-06

How to Cite

Muhammad Achsan Hujjatul Islam, & Muhtadin. (2026). Komputasi Paralel untuk Mendeteksi Gelombang QRS Complex Menggunakan YOLO Deep Learning. Journal of Computer Engineering, Network, and Intelligent Multimedia, 2(3). https://doi.org/10.59378/jcenim.v2i3.62

Issue

Vol. 2 No. 3 (2024)

Section

Articles

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Copyright (c) 2026 Muhammad Achsan Hujjatul Islam, Muhtadin

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