Inventory of goods is a problem that is often faced by companies. Inventory of goods can provide positive and negative effects, such as the amount of inventory that does not meet costumer desires it can make consumers disappointed and can move to other traders. Problems that occur at PT. Putra Preneur Mitra Makmur Abadi Banjarbaru is in managing data items still using manual methods by writing into a notebook. The application of the  K-Nearest Neighbor Regression method in predicting outgoing goods at PT. Preneur Mitra Makmur Abadi’s son, Banjarbaru, can optimize the order of goods so that there is no shortage or excess stock in the warehouse of PT. Putra Preneur Mitra Makmur Abadi Banjarbaru. In the case of this study, the K-Nearest Neighbor Regression method can be applied to the prediction of outgoing goods at the PT. Putra Preneur Mitra Makmur Abadi Banjarbaru because the accuracy of the test value obtained by the MAD method is less than 1 and with the values of k = 3, 4, and 5. Where the optimal k-value in the K-Nearest Neighbor Regression method for goods prediction at Gudang PT. Preneur Mitra Makmur Abadi Banjarbaru’s son is 5 and the prediction of the expenditure of goods using k-optimal (5) in the K-Nearest Neighbor Regression method is seventeen variants as follows; greentea 0.90, thaitea 0.28, 0.25, red velvet 0.38, avocado coffe 0.00, cappucino 0.38, caramel coffe 0.00, creamy coffe 0.23, choco creamy 0.15, choco durian 0.00, choco royal 0.45, vanilla 1.03, wine 0.13, blueberry 0.33, score 0.10, mango 0.38, and have an average value of 0.293.

Keywords: Inventory, Prediction, K-Nearest Neighbor Regression