Penerapan Metode K-Means Clustering Untuk Menentukan Pola Penjualan Kue Pada Alfaza Bakery - Riki Yohanes Hendriyanto; Lely Hiryanto (Fakultas Teknologi Informasi Universitas Tarumanagara, 2023)
The home industry is a type of small-scale business activity that is often found in villages and around houses, both in urban and rural areas. Starting from an association of the same people who studied to pursue the field of making cakes and bread and who then wanted to expand the sales area and create jobs for residents. the obstacle faced is ignorance of the products that are purchased the most and in which areas certain products run out the fastest, it is necessary to do data mining analysis using the clustering method. The K-Means method is a data clustering method using observation based on the similarity of the objects studied. A cluster is a collection of data that has similarities in its members or is different from other groups, clusters are used to minimize variation within a cluster and maximize variation between clusters, in other words data that has attribute similarities between one another and attribute differences to other clusters, determines the right cluster by using the elbow method which can maximize the quality of clusters so that the clusters are more varied. The results of testing this study with the elbow method obtained the right number of 4 clusters, then the clustering results with the most sales were obtained in cluster 3, cluster 1 with moderate sales, cluster 0 with few sales and cluster 2 with the least sales.