Jurnal Publikasi STMIK Pontianak

Data Mining Untuk Klastering Dataset Multidimensional Menggunakan Algoritma Ant Colony Optimization

Abstrak

Right now data mining activities are still hidden to further processed into useful knowledge in decision making. The process of information extraction from the collection of data that is stored with the data mining. One of the methods in Data Mining is clustering. Clustering aims to segment the physical or abstract objects in the form of classes or objects similar to the One is ACO (Ant Colony Optimization). On this research analyzed the influence of the changes made on the application of the level of accuracy and the resulting clusters, and system parameters that apply. For the purpose of software is built as a media test ACO algorithm. Level of accuracy can be improved by using pheromone and increase the value of the parameter and the maximum number of ant Iterations. But the more and the maximum number of ant addition, with improved Iterations then processing time will be longer.

Keywords: Data Mining, Clustering, Ant Colony Optimization, Cluster Analysis.