Enhanced tele ECG system using Hadoop framework to deal with big data processing

M. Anwar Ma'Sum, Wisnu Jatmiko, Heru Suhartanto

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

Indonesia has high mortality caused by cardiovascular diseases. To minimize the mortality, we build a tele-ecg system for heart diseases early detection and monitoring. In this research, the tele-ecg system was enhanced using Hadoop framework, in order to deal with big data processing. The system was build on cluster computer with 4 nodes. The server is able to handle 60 requests at the same time. The system can classify the ecg data using decision tree and random forest. The accuracy is 97.14% and 98,92% for decision tree and random forest respectively. Training process in random forest is faster than in decision tree, while testing process in decision tree is faster than in random forest.

Original languageEnglish
Title of host publication2016 International Workshop on Big Data and Information Security, IWBIS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages121-126
Number of pages6
ISBN (Electronic)9781509034772
DOIs
Publication statusPublished - 6 Mar 2017
Event2016 International Workshop on Big Data and Information Security, IWBIS 2016 - Jakarta, Indonesia
Duration: 18 Oct 201619 Oct 2016

Publication series

Name2016 International Workshop on Big Data and Information Security, IWBIS 2016

Conference

Conference2016 International Workshop on Big Data and Information Security, IWBIS 2016
Country/TerritoryIndonesia
CityJakarta
Period18/10/1619/10/16

Keywords

  • Hadoop
  • Tele-ecg
  • big data
  • decision tree
  • random forest
  • request
  • server

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