Memprediksi Kualitas Produk Inspeksi Dalam Meminimalisasi Resiko Produk Ng Meggunakan Algoritma Regresi Linier - Dini Rahayu; Aris Gunaryati (Bulletin of Information Technology (BIT), 2023)
Predicting the product is a form of analyzing data, predicting the product is an important factor that determines the smooth running of the product. Utilization of product and defect data can be used in carrying out the process of data mining and modeling stages to predict the number of product defects at one time. The application of the simple Linear Regression algorithm equation model can be implemented where the results also provide a new insight for the prediction needs of the number of product defects. The simple Linear Regression equation model after comparison with actual calculation results (observations) and also with the Rapid Miner application in general shows similar results. Evaluation and testing of the RMSE value was also obtained when evaluating the applied linear regression model, with an RMSE value of 0.984 with a standard deviation of +- 0.0