Penerapan Algoritma Topsis untuk Perekrutan Karyawan Divisi HRD pada CV. Semito Mandiri - Andriyansyah Andriyansyah; Siswanto Siswanto; Mujito Mujito (Ikatan Ahli Informatika Indonesia, 2019)
The company implements strict employee recruitment selection for job applicants to suit the company's needs to get quality human resources. The process of selecting prospective employees is done by checking and selection manually by looking at the files sent by applicants. This is of course not only very troublesome but also inefficient and takes a long time, not to mention the possibility of human errors and subjective judgments so that the chosen candidates are not the best candidates. Utilizing a Decision Support System that uses the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) Algorithm can help the selection selection problem in the Human Resource Development (HRD) division. So the results of this study are the ranking process with TOPSIS get the average distance between manual results with TOPSIS of 3.5 with a standard deviation of 2.813 and the classification process with Naïve Bayes produces an accuracy of 77.78% and an error of 22.22%, with the error value the results of the classification still have shortcomings in predicting the eligibility of prospective employees.