Performance Analysis of Tree-Based Algorithms in Predicting Employee Attrition

Based on data throughout 2022, there have been many reductions in employees both globally and Indonesia. The reduction was made due to adjustments with developments keep the business afloat increasingly fierce competition. However, reducing number of is not an easy decision make. This can impact aspects development course a or company. To make especially related aspect termination employment, it necessary consider carefully thoroughly. Assessment decision-making cannot be based just one aspect, other need seen taken into consideration. Additional that selected strengthen from data. Data will any value without processing various approaches, which prediction process. Starting data, results more appropriate decision. study comparison 3 tree algorithms, produced three methods terms accuracy. this are best accuracy for each algorithm C.45 = 83.44; Random Forests 85.85; LMT 88.29 linear precision value, model highest Logistic Model Tree (LMT) algorithm.