Implementation of Intelligent Searching Using Self-Organizing Map for Webmining Used in Document Containing Information in Relation to Cyber Terrorism

Abstract

The terrorism activities are not only in real world as development of technology, but also in cyber world. Terrorism activities in cyber world are called cyber terrorism. One of methodology for cyber terrorism detection is by applying data mining algorithm to textual content of terrorism related web pages. Web mining is technology applied to extract information from the web. By using web mining, cyber terrorism information will be collected from internet. This research aims to use text cluster technique, by which the web documents are clustered using Self-Organizing Map algorithm based on number of occurrences of the certain words in documents that have relevance to cyber terrorism. The result shows mapping of the clustered documents that have performance 6.1 and 22.75 in term of vector quantization error (VQE). According this result, we concluded that Self-Organizing Map (SOM) is able to visualizethe topology of the data, by converting statistical relationship among the data into simple geometrical relationship of their image points in 2-dimensional grid.