Prediksi Jumlah Kasus Klaim Indemnity Dengan Menggunakan Algoritma Regresi Linear Pada Asuransi Mandiri Inhealth

Abstract

Insurance is a type of financial institution that aims to provide guarantees to customers against risks that may occur in the future. In this study, by utilizing some data on indemnity claim cases on inhealth insurance through a prediction method approach and can be applied in analyzing data to make predictions of future insurance data based on the level of need. The prediction process of a simple Linear Regression algorithm can be implemented where the results also provide new insights for the prediction needs of claim data. Tests using rapidminer produce performance that is relevant to the scenario being modeled. The simple Linear Regression equation model after comparing the results of calculations manually and also with the Rapid Miner application generally shows the same data. The RMSE value is also obtained when evaluating the performance of the applied model, with an RMSE value of 0.273 with a standard deviation of +- 0.0.