Penerapan Algoritma K-Means Clustering Dalam Pengelompokan Data Penjualan Pada Pabrikan Mobil Toyota Indonesia
Abstract
Abstrak Data Mining merupakan upaya untuk mengeksplorasi data yang telah dipilih dengan tujuan menemukan wawasan dan pengetahuan yang bermanfaat. Metode Clustering merupakan pendekatan non-hirarki yang digunakan untuk memisahkan objek-objek ke dalam satu atau lebih Cluster berdasarkan karakteristik data. Saat ini Algoritma K-Means Clustering banyak digunakan pada perusahaan - perusahaan berskala besar pada tahun 2022 perusahaan mobil Toyota telah menjual 300 ribu lebih unit mobil dari semua type, Hasil dari klasterisasi berakhir sampai iterasi ke 11 karena pada iterasi 11 mendapatkan hasil yang sama dengan iterasi sebelumnya yaitu iterasi 10, Dalam pengelompokan penjualan mobil, terdapat tiga kelompok, yaitu C0 (Kurang Diminati), C1 (Diminati), dan C2 (Sangat Diminati). dapat di lihat pada Tabel 4.20. Dari kelompok mobil yang ada dapat dilihat bagaimana tingkat minat konsumen atau pembeli terhadapan produk mobil toyota sehingga perusahaan dapat menyesuaikan produk mana yang ingin dijadikan prioritas untuk dipasarkan, untuk mobil-mobil yang kurang diminati perusahaan bisa melakukan evaluasi baik dari segi kualitas produk, pemasaran, iklan, dan harga yang kompetitif sehingga dapat menimbulkan daya tarik bagi pembeli serta mampu bersaing dengan kompetitor-kompetitor produk sejenis. Kata kunci: Data Mining, Algoritma K-Means Clustering, RapidMiner, Penjualan Mobil Toyota Abstract [Application of the K-Means Clustering Algorithm in Grouping Sales Data at the Indonesian Toyota Car Manufacturer]. Data Mining is an attempt to explore selected data with the aim of finding useful insights and knowledge. The Clustering method is a non-hierarchical approach used to separate objects into one or more clusters based on data characteristics. Currently, the K-Means Clustering algorithm is widely used in large-scale companies in 2022 the Toyota car company has sold more than 300 thousand units of cars of all types, The results of clustering end until the 11th iteration because in iteration 11 it gets the same results as the previous iteration, namely iteration 10, In the grouping of car sales, there are three groups, namely C0 (Less Desirable), C1 (Desirable), and C2 (Highly Desirable). can be seen in Table 4.20. From the existing car group, it can be seen how the level of consumer interest or buyers in front of Toyota car products so that the company can adjust which products want to be a priority to be marketed, for cars that are less desirable the company can evaluate both in terms of product quality, marketing, advertising, and competitive prices so that it can cause attraction for buyers and be able to compete with competitors of similar products. Keywords- Data Mining, Algoritma K-Means Clustering, RapidMiner, Toyota Car SalesDownloads
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