Implementation of Selection of Employee Candidates By Utilizing Social Media Using Linear Regression Algorithms and Topsis Methods: A Case Study of A Boarding School

Efficiency in the selection of prospective employees can have a significant impact on increasing costs and extending the time required in the recruitment process of HR Information Systems in boarding schools. However, the hiring process is often still done manually and traditionally, resulting in high costs and time and lack of efficiency. Social media has become an important part of modern society, including in the employee recruitment and selection process. Social media can be used to obtain more comprehensive information about prospective employees, such as educational background, skills, work experience, and personality. This research investigates using Linear Regression Algorithm on social media classification and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method as ranking criteria in classifying prospective employees. One of the proposed solutions is to utilize information from social media to evaluate the potential and personality of prospective employees. This research specifically reviews the application of Linear Regression Algorithm and TOPSIS method in categorizing prospective employees based on information obtained from social media, focusing on HR Information System in a particular boarding school. The results showed that the application of social media classification system with linear regression algorithm with Mean absolute error 10.50, Residual sum of squares (MSE): 147.16, R-squared: 1.0 and TOPSIS method with an accuracy rate of 0.51238 for the first rank can improve the efficiency of the recruitment process