Deby Putri Indraswari
Universitas Brawijaya

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Journal : Journal of Enviromental Engineering and Sustainable Technology

SISTEM PENDUKUNG KEPUTUSAN DETEKSI DINI PENYAKIT STROKE MENGGUNAKAN METODE DEMPSTER-SHAFER Deby Putri Indraswari; Arief Andy Soebroto; Eko Arisetijono Marhaendraputro
Journal of Environmental Engineering and Sustainable Technology Vol 2, No 2 (2015)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (570.575 KB) | DOI: 10.21776/ub.jeest.2015.002.02.6

Abstract

Stroke is a neurological function disorders caused by impaired blood flow in the brain. Stroke is the third most common cause of death in developed countries, after heart disease and cancer. This causes a stroke to watch. Early prevention through medical examination needs to be done to reduce the high rate of risk of stroke. The detection of the risk of stroke is determined when knowing the criteria of risk factors is complete and structured. But sometimes the detection of the risk of stroke is difficult to determine if there are risk factors that have forgotten or not structured so that doctors can experience problems or ambiguous to make diagnosis. To overcome the problem of semi-structured pattern, it can be solved using decision support systems (DSS) with intelligent computing. SPK early detection of stroke constructed using methods Dempster Shafer. In the study can detect the level of risk of stroke is high risk, medium, and low with 8 input risk factors. Based on the data used in this system is obtained accuracy of 90%. So that it can be concluded that SPK is constructed with Dempster Shafer method to function well for detecting stroke.