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The Spreading Prediction of Dengue Hemorrhagic Fever (DHF) in Bandung Regency Using K-Means Clustering and Support Vector Machine Algorithm

机译:基于K均值聚类和支持向量机算法的万隆登革热出血热传播预测。

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Dengue Hemorrhagic Fever (DHF) is the health problem that exist in tropical country, includes Indonesia. Especially for the Bandung Regency, DHF sufferers fluctuated in the last three years. Through data by Health Department of Bandung Regency recorded from 2014 to 2016, in 2014 recorded as many as 524 cases, in 2015 as many as 1,017 cases, and then in 2016 as many as 3476 cases. Many factors that cause people become DHF sufferers in Bandung Regency are constantly increasing, some of them are high rainfall and also lack of awareness of the cleanness. In this research presents the research about the prediction of DHF in Bandung Regency using K-Means Clustering as preprocessing method and Support Vector Machine (SVM) algorithm as classification method according to historical data of DHF and weather data from BMKG (Meteorological, Climatological, and Geophysical Agency) in Bandung Regency from 2009 until 2016 using the dot and radial kernels on the SVM algorithm. The radial kernel obtains testing accuracy up to 93%, while the kernel dot obtains average of testing accuracy 62%.
机译:登革出血热(DHF)是热带国家(包括印度尼西亚)存在的健康问题。尤其是对于万隆摄政区,近三年来,DHF患病者的人数有所波动。根据万隆摄政局卫生部门2014年至2016年记录的数据,2014年记录了524例,2015年记录了1,017例,然后在2016年记录了3476例。在万隆摄政区,许多导致人们成为DHF受害者的因素正在不断增加,其中一些是高降雨,也缺乏清洁意识。本研究根据DHF的历史数据和BMKG的气象,气象和气候资料,以K-Means聚类为预处理方法,并采用支持向量机(SVM)算法为分类方法,对万隆摄政区的DHF进行了预测。 (2009年至2016年)在万隆摄政区的地球物理局),使用SVM算法上的点和径向核。放射状内核获得高达93%的测试精度,而内核点获得的平均测试精度为62%。

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