PENGARUH PENENTUAN CENTROID AWAL MENGGUNAKAN ALGORITMA ANT COLONY OPTIMIZATION TERHADAP HASIL PENGKLASTERAN DATA BERDIMENSI TINGGI

NISA', IMAS SHAIBUN and Jambak, M. Ihsan (2020) PENGARUH PENENTUAN CENTROID AWAL MENGGUNAKAN ALGORITMA ANT COLONY OPTIMIZATION TERHADAP HASIL PENGKLASTERAN DATA BERDIMENSI TINGGI. Undergraduate thesis, Sriwijaya University.

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Abstract

Data Clustering can be done in several methods, one of which is the K-Means method. K-Means is a popular method of data clustering because of its simple implementation, it can handle large amounts of data and a relatively short process. In the k-means algorithm, initial centroid initialization is usually generated randomly, initial centroid initialization which is generated randomly often results in an optimum local solution. The optimum local solution has an impact on the quality of the clustering results being poor. Therefore it is necessary to find conditions that can meet the optimum global conditions where exploration occurs for the entire search space. Ant Colony Optimization (ACO) is an ant algorithm in forming a colony. The ACO algorithm can avoid optimal local problems and have proven global solutions. In this research, an algorithm for ACO and K-Means-based data clustering is applied. The ACO algorithm can avoid optimal local problems and have proven global solutions. Based on the reliability of the ACO method in finding the optimum global solution, this paper tries to raise the ACO Algorithm as a reference for further action aimed at testing the effect of the ACO method in determining initial centroids on the quality of the results of the k-means clustering results

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	K-means, Pengklasteran, Ant Colony Optimization, Pusat Klaster, Lokal Optimum, Global Optimum.
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Users 7819 not found.
Date Deposited:	04 Sep 2020 05:22
Last Modified:	04 Sep 2020 05:22
URI:	http://repository.unsri.ac.id/id/eprint/34514

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