Prediksi Penyakit Diabetes Untuk Pencegahan Dini Dengan Metode Regresi Linear - Niko Suwaryo Niko; Arif Rahman; Dewi Marini Umi Atmaja; Amat Basri (Forum Kerjasama Pendidikan Tinggi (FKPT), 2023)
Estimation is a method in which we can estimate the population value by using the sample value and which can model an equation to calculate the estimate i.e. a linear regression algorithm attempts to model the relationship between two variables by fitting a linear equation to observe the data. The application of a simple Linear Regression algorithm model can be implemented well and is able to provide a new insight for the need for predictions about the condition of diabetes data quality in controlling sugar levels in the body. Predictions of diabetes in the future can be known through the use of datasets using a prediction method approach through structured stages in analyzing the data used to produce an RSME value when evaluating a model of 0.000 +/- 0.000. Performance testing of the models and algorithms used in the evaluation can produce a picture that is relevant to the scenario being modeled. The RMSE value is obtained when evaluating the model performance of 0.000 +/- 0.000 through the RapidMiner Studio application.