Real Time Detection of Employee Satisfaction Level based ANFIS Method and Internet of Things

Abstract

Job satisfaction is an important factor in human resource management in an organization. Job satisfaction can affect productivity, performance, and loyalty. In this study, the level of job satisfaction will be predicted based an Adaptive Neuro Fuzzy Inference System model in real time supported by Internet of Things. Based on model validation, the results obtained were that the variables of performance appraisal, work motivation, facilities and work environment, responsibility, and competence has an effect on job satisfaction with an accuracy rate of 97.18%.