PENGKLASTERAN AREA PEMBANGUNAN BAK SAMPAH DAUN MENGGUNAKAN METODE K-MEANS
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Date
2021-02
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Abstract
The area around Riau University has a lot of leaf litter because the area is
overgrown with trees, but currently the destruction of leaf litter scattered only done
by burning. This is because there is no leaf garbage tub available in riau university
environment and also there has not been an analysis of the grouping of areas that
have the potential for the construction of the leaf garbage tub. From the existing
problems, it can be seen that Riau University needs analysis of the grouping of areas
to determine the grouping of areas in building garbage cans. Therefore, this research
aims to implement the k-means clustering algorithm in conducting cluster analysis to
determine the group of areas in building garbage bins that exist in the area of Riau
University. This study reviewed data in the form of 71 data point location of leaf
garbage stacks with data attributes clustered are latitude points and longitude of data
objects. The research phase that emphasizes the analysis of k-means clustering goes
through 2 stages, namely the process of clustering with k-means, and the testing of
clustering results with silhouette coefficient, The clustering process is carried out by
experimenting the number of different clusters, namely 3, 4, 5, 6, and 7 clusters. The
best cluster results testing is done using the silhouette coefficent method. Based on
the results of the experiment, the number of k=3 is the best cluster with test results of
0.5906023241609282. This means that as many as 3 garbage can be built in the area
around the centroid point of each cluster
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Keywords
Clustering, Data Mining, K-Means, Python, Leaf Litter