@inproceedings{5fc2b46252414fa6bb36e0f4c78a77a9,
title = "Enhanced tele ECG system using Hadoop framework to deal with big data processing",
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.",
keywords = "Hadoop, Tele-ecg, big data, decision tree, random forest, request, server",
author = "Ma'Sum, {M. Anwar} and Wisnu Jatmiko and Heru Suhartanto",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 International Workshop on Big Data and Information Security, IWBIS 2016 ; Conference date: 18-10-2016 Through 19-10-2016",
year = "2017",
month = mar,
day = "6",
doi = "10.1109/IWBIS.2016.7872900",
language = "English",
series = "2016 International Workshop on Big Data and Information Security, IWBIS 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "121--126",
booktitle = "2016 International Workshop on Big Data and Information Security, IWBIS 2016",
address = "United States",
}