Design and Analysis of Human Resources Using Artificial Intelligence

Abstract

Objective: Artificial intelligence makes it simpler to decide things and to rectify the flow of organizational procedures and actions, making it easier to examine the work happiness of staff members and enhancing management with only a range of tasks, work styles, and surroundings. To ensure that the firm hires and retains talented personnel in light of the rise in international business operations and the number of companies expanding into export firms, people management is required. Organizations have struggled to find qualified experts to perform the necessary training and assignments for a very long time. This study's objective is to develop an automated system for measuring job satisfaction but use an improved neural network methodology. Method: The data analysis is performed based on a variety of variables, including the number of workers, the total amount of employees by industry, the total number of employees by income range (lower, moderate, higher), and the total number of workers by the department as well as salary range. Results: The most important characteristics, such as the degree of comfort, the most recent review, the number of events, the typical number of hours worked each month, and staff members with a little more than ten years of service, are identified. As a method of improvement, the Genetic Algorithm is used to increase the quality of characteristics. Conclusions: Artificial Neural Networks are used to estimate the satisfaction levels of employees by feeding them the best qualities as input data. Analysis of the suggested work's enhancement in accuracy, recall, as well as F-measure has just been done in that order.