OPTIMASI NILAI KLASTER PADA ALGORITMA K-MEANS MENGGUNAKAN ALGORITMA FIREFLY

W, FEBIYANTI and Rini, Dian Palupi (2024) OPTIMASI NILAI KLASTER PADA ALGORITMA K-MEANS MENGGUNAKAN ALGORITMA FIREFLY. Undergraduate thesis, Sriwijaya University.

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Abstract

K-Means is one of the most commonly used clustering algorithms for grouping data with similarities within a cluster. However, there are limitations in K-Means clustering, such as clustering results being initialized based on random centroid points and the number of clusters used. To improve the performance of the K-Means algorithm, the Firefly Algorithm is used for clustering optimization. The Firefly Algorithm offers flexibility in parameter determination and can deliver excellent performance. In the testing phase, the best optimization values with the Firefly Algorithm were obtained with the number of iterations = 60, α = 0.1, β_0 = 0.1, and γ = 0.01. This study shows that optimizing the Firefly Algorithm for K-Means clustering can improve clustering results, using the Silhouette Score as a benchmark. The closer the Silhouette Score is to one, the better the clustering result. The Silhouette Score for K-Means was 0.381, while the result for K-Means clustering optimized with the Firefly Algorithm was 0.431.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Clustering, Optimization, K-Means, Firefly Algorithm
Subjects:	T Technology > T Technology (General) > T1-995 Technology (General) T Technology > T Technology (General) > T1-995 Technology (General) > T313.I55 Indonesia (Table T6)
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Febiyanti W
Date Deposited:	15 Jul 2024 04:04
Last Modified:	15 Jul 2024 04:04
URI:	http://repository.unsri.ac.id/id/eprint/150630

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