Penerapan Data Mining Untuk Memprediksi Penjualan Bahan Bakar Minyak Menggunakan Algoritma K-Means Clustering (Studi Kasus: PT. Anugerah Alam Semesta) - Rahayul Kahfi; Muhammad Syahrizal (Forum Kerjasama Pendidikan Tinggi (FKPT), 2020)
Business is always traversed by competing all companies always thinking of ways to make the company always go forward and the company can continue to survive in developing the business if the company will not decline. The company wants to know the number of sales at PT. Anugerah Alam Semesta Raya to obtain the most popular sales data analysis for the sale of fuel types. One of the factors in clustering the sale of fuel oil is to facilitate the sale of fuel oil by means of grouping. One problem in inventory is the difficulty in determining the large amount of inventory that must be provided in meeting the demand. It often happens that a company has too little inventory compared to consumer demand. Reviewing the company directly regarding the process of selling fuel at the company by processing it by clustering the previous sales data to produce a prediction about further sales in order to be better. Unstable sales will result in a company's precenomian can be weakened with the word another company must obtain a technique in terms of managing sales of fuel oil in the future, so that it can produce a prediction with good accuracy in drawing a conclusion