CLUSTERING SEARCH KEYPHRASE DENGAN METODE NEAREST NEIGHBOUR

Abstract

Search keyphrase represent the needs or interests of users of an information or a topic in a web site. For web manager, search keyphrase can be used as an evaluation of whether the user has a need or interest in accordance with web content that is owned, also can be used as a basis in determining the marketing strategy. Problems in search keyphrase analysis is the diversity and amount of data is very large. Analysis manually takes a long time. Energy and the human mind is also limited in analyzing large data resulting accuracy of the analysis results to be reduced. Solution to overcome the problem of search keyphrase analysis, is to do a search keyphrase clustering into several groups. Search keyphrase that has similarities to be grouped in one group called clusters. Web manager easier in the analysis, because it does not need to see all the data, simply look at each cluster to determine the needs of the user. One method is nearest Neighbor clustering, where the distance between two clusters is calculated as the distance between the two closest elements in the two clusters. Nearest Neighbour included in the category of agglomerative hierarchical clustering. The advantages of the method lies in the nearest neighbor cluster results in the form of hierarchy. Each level of the hierarchy of clusters can be considered to represent the topics and sub-topics of interest to the user