Clustering Time Series Data Mining dengan Jarak Kedekatan Manhattan City

Abstract

The development of information technology is very rapid and is supported by the development of storage media technology and its application to all fields that produce huge amounts of data stacks generated from various sources, therefore need new techniques in managing data stacks. Data mining has become very important as an object and research study at this time because there are many data stacks found in agencies. Data mining is an analytical process of knowledge discovery in large and complex data sets. In this study the technique used is to conduct time series data mining clusters, using proximity to manhattan city. The time series graph is carried out by the sliding window to produce an analysis of the window for each cluster result. Based on cluster results, an analysis of knowledge transformation is carried out into new knowledge obtained from data mining time series data.