IMPACT OF ARTIFICIAL INTELLIGENCE IMPLEMENTATION ON AIRCRAFT MAINTENANCE OPTIMIZATION THROUGH ANOMALY DATA CENTER DETECTION

Abstract

This study aims to determine the impact of Artificial Intelligence (AI) implementation on aircraft maintenance optimization through data center anomaly detection at PT GMF Aeroasia. The data used in this research is primary data, taken from the answers of 32 respondents, namely maintenance division employees at PT GMF Aeroasia with saturated sampling technique. This research uses a quantitative approach and uses Structural Equation Modeling-Partial Least Square (SEM-PLS) analysis techniques to determine the impact of implementing AI on aircraft maintenance optimization through data center anomaly detection on GMF. The results showed that there was a positive and significant impact of artificial intelligence implementation and anomaly data center detection on aircraft maintenance optimization both partially. This research can enhance aircraft maintenance efficiency, predict potential issues, boost passenger safety and comfort. Additionally, it can contribute to the understanding of AI and anomaly detection in optimizing aircraft maintenance.