Klasifikasi Algoritma K-Nearest Neigbhor Untuk Memprediksi Barang Pada PT Enesis Group - Adi Muhajirin; Sastro Atmojo Sasosno; Truly Wangsalegawa (Program Studi Informatika, Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya, 2021)
The company's success in maintaining its business is inseparable from the company's role in managing inventory (inventory) of goods so that it can meet the demands of customers as much as possible. During this time at PT. Enesis Group for data collection in warehouses is still carried out by keeping a manual in the book, which causes the accumulation of documents and the risk of loss or damage to documents when the item data is needed to make a report to superiors and also as a performance evaluation aterial. Often there is a lack of goods / reject goods. Do not have a computerized system. In the case of this study, the K-Nearest Neighbor method can be applied to the prediction of goods going out at the warehouse of PT. Enesis Group because it can predict the goods out correctly so that there is no shortage or excess stock of goods in the warehouse. The results of the calculation of the prediction of goods going out with the KNN method with an optimal value of K (9) are for ordering goods with a shipping distance of more than 1000 km and the expiration of goods more than 1 year, as well as for ordering goods with a distance of less than 1000 km and the expiration of goods is less from 1 year, the item is eligible to send.