Analysis of the K-Nearest Neighbor Algorithm to Determine the Prediction of Tofu Production - Munif Munif; Mustain Mustain; Kurnia Yahya (Universitas Nahdlatul Ulama Surabaya, 2022)
The tofu factory in Kedungpring does not yet have a prediction system to estimate the number of tofu that will be predicted for the next month. As a result, companies cannot meet market demand in a timely and appropriate amount. Therefore, it is necessary to make a prediction system to determine the amount of tofu production in Kedungpring District. In this research, the application of K-Nearest Neighbor Algorithm Analysis Application to determine the prediction of the number of Web-Based production to make it easy to predict the number of tofu production. The system functional test results show that all features in the application are able to run properly and functionally. Testing the accuracy of the prediction system K-Nearest Neighbor algorithm to determine the prediction of the number of web-based tofu production that can produces a MAPE of 0.68%