CD Skripsi
Pengklasteran Area Pembangunan Bak Sampah Daun Pada Universitas Riau Menggunakan Metode K-Means
The area around Riau University has a lot of leaf litter due to its very large area,
but currently the leaf waste scattered is only done 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 kmeans
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 coeffisien. The clustering process is carried out by
experimenting the number of different clusters, namely k=3, k=4, k=5, k=6, and
k=7. The best cluster results testing is done using the silhouette coeffisien 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.
Keywords : Clustering, Data Mining, K-Means, Python, Leaf Litter.
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