Text Classification Using Support Vector Machine for Webmining Based Spatio Temporal Analysis of the Spread of Tropical Diseases

Tropical diseases such as Dengue Fever, Malaria and Bird Flu have become epidemic and particular problem in Indonesia. As the number of such cases increases, the availability of information regarding these diseases is important in order to help experts in taking proper actions. Meanwhile, web mining is one of significant technologies applied to extract information from the web. By using web mining, spatio-temporal information of tropical diseases will be collected from the internet. The objective of this study is to develop text classification system using Support Vector Machine to classify the Indonesian textual information on the Web. Proper classification for every downloaded text document helps the information extraction system to construct spatio-temporal analysis so then can be visualized. While Support Vector Machine has shown its capabilities for classifying text since it works well in high-dimensional data and avoids the curse of dimensionality problem.