Check On-Time Performance of Domestic Airlines Using Random Forest Machine Learning Analysis

Abstract

This study aims to analyze the On-Time Performance on domestic flights in Indonesia using the Random Forest machine learning analysis method. The purpose of this study is to predict On-Time Performance on domestic flights with high accuracy. The data used in this study are questionnaire data  and factors that affect On-Time Performance on domestic flights in Indonesia. The results showed that the Random Forest model can produce On-Time Performance predictions on domestic flights with a high level of accuracy. Factors such as ground handling services, weather, and technical operations have a significant influence on On-Time Performance on domestic flights. The implication of this research is that it can help airlines optimize flight schedules and minimize flight delays, thus providing satisfaction to passengers