Analysis of C4.5 and K-Nearest Neighbor (KNN) Method on Algorithm of Clustering For Deciding Mainstay Area
Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2016, Vol 18, Issue 2
Abstract
Development as a sustainable activity needs a good plan, so the programs can be effective and have a clear objective. Therefore, a model to help the analysis is significantly needed in determining the priority area to conduct better development in the future. This research applies the concept of Klassen Typology to analyze PDRB data in Papua Province. Based on the result of using Klassen typology analysis method, there are 4 (four) quadrants of area classification in Papua Province. Twenty nine regencies were analyzed based on PDRB data to investigate which area can be used as the development of priority area in the future. The method used in this study is C4.5 and k-nearest neighbor . Time complexity becomes test standard of a particularalgorithm to get efficient execution time when implemented into programming language. The approach of asymptotic analysis using the concept of Big-o was one of the techniques that are usually used to test time complexity of an algorithm. Based on the testing result of both methods, it shows that the result of running time of KNN is more stable than of C4.5 although the analysis of Big-O gives complexity of the same time.
Authors and Affiliations
Heru Ismanto , , Retantyo Wardoyo
Keywords
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