Saudi Airlines Cabin Crew Performance Appraisal Using Artificial Intelligence - The Adaptive Neuro-Fuzzy Inference System

Abstract

This paper targets the application of artificial intelligence in improving and developing performance through the reduction of human error and the development of fair judgment in the performance of different activities. It focuses on Adaptive Neural Fuzzy Inference System (ANFIS) for the Saudi Airlines cabin crew. Among the findings of the research was that the training error is that the difference between the training data output value and the output of the fuzzy inference system and that the fuzzy linguistic variables are not clear when applied in the performance evaluation system. The study applied a case study to analyze an adaptive neural inference system and rate it to the impact it could create on the cabin crew. The study concluded that in conducting the performance appraisal of the employees some factors such as work goals, and information on the effectiveness of goals must be considered. Also, the lack of a formal reasoning mechanism supporting the inference and evaluations is a critical challenge in performance appraisal; hence, the application of artificial intelligence in the evaluation of the performance of employees in an organization could significantly impact the employees in working towards a common goal.