Komparasi Algoritma Logistic Regression dan Random Forest pada Prediksi Cacat Software

Abstract

Testing becomes the standard in producing quality software, testing can be assessed through certain measures and methods, one of the benchmarks for software quality is ISO, which was made by the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC) , In the prediction of software defects software defect prediction error is a very bad thing, the prediction results can have an effect on the software itself. This study compares the results of the Logistic Regression Algorithm and Random Forest before and after the resampling method is applied, the test results show that Random Forest with resampling produces a higher level of accuracy. From the test results above, it can be concluded that the Random Forest with resampling method is more effective in predicting software defects