PENERAPAN DATA MINING JUMLAH PENJUALAN SEPEDA MOTOR MENGGUNAKAN METODE K- MEANS CLUSTERING (Studi Kasus : PT. Tunas Dwipa Matra Way Kanan)

Fitri Anggraini, Rustam Rustam, Sidik Rahmatullah, Supriyanto Supriyanto

Abstract


With the ever-expanding product spectrum of motorcycles, as we all know, motorcycles are a popular form of public transportation because of their practicality. The motorcycle business had to develop further and adopt new technologies. The motorcycle market in Indonesia is currently flooded with motorcycle companies, including Honda, Yamaha, Suzuki and Kawasaki, which are constantly competing to win consumer interest in buying motorcycle products. It is difficult for staff to set sales forecasts because of the volume of motorcycle sales data. In processing motorcycle sales data, it is necessary to carry out a data grouping technique. Using the K-Means method will divide and classify data into predetermined clusters by grouping based on certain classes. A data that has the closest similarity will be in the same cluster. Processing motorcycle sales data with this method can determine the amount of sales. The tools used in this research are Google Colaboratory. In this study there are 3 clusters. The results of this study are cluster 1 (many) there are 4 data in data 1, 2, 3 and 4, in cluster 2 (moderate) there are 3 data in data 5, 6 and 7, and cluster 3 (less) there are 5 data in data 8, 9, 10, 11 and 12. In the application of data mining using google colaboratory there are 3 colors namely yellow (cluster 1) there are 4 data, purple (cluster 2) there are 3 data and blue (cluster 3) there are 5 data. So it can be concluded that manual calculations using the k-means clustering method and the application of data mining using the Google colaboratory are relevant.

Keywords


Motorcycles, Data Mining, K-Means Clustering, Google Colaboratory

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DOI: https://doi.org/10.30873/ji.v24i1.3685

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