DATA MINING ALGORITMA C4.5 UNTUK MEMPREDIKSI PENJUALAN BATERAI DI PT VARTA MICROBATTERY INDONESIA - Wijaya, Bagus; Fauzi, Rahmat (Computer Science and Industrial Engineering, 2020)
The development information of technology in the current era of globalization is very fast, this requires all companies in the world to be able to compete with each other. The competition in the bussiness world, forcing all of the companies to think of strategies and breakthroughs that can ensure the sustainability of the bussiness that they run of. PT VARTA MICROBATTERY INDONESIA is a company engaged producing battery-based materials. However, looking at the past years many series of battery models have been discontinued. Some series of battery models that have been stopped production. It’s difficult to obtain strategic information such as the level of sales per period, predictions of sales in the coming years, and sales of products produced. Availability large sales data in the database server are often not used optimally, therefore the sales data is only used for daily operational activities. Analysis is needed to see patterns from sales data so as to produce predictions of battery. That big data from customer can be analysis using data mining. The method to use as for predictions is C4.5 Algorithm based on decision tree. This mining activity is expected to provide a decision tree to see patterns of prediction consumer buying behavior the batteries. The results of this mining activity is getting 9 rules with size category knowing as a root and the sales via as a leaf.