Employees are an important element in a company that determines the progress of a company. With good quality employees in a company, it is easier to achieve desired goals of a company. Conventional (manual) recruitment method is vulnerable to non-technical factors such as frequent duplicate data or invalid data. In such condition, a Decision Support System (DSS) will be helpful in making decision process valid and reliable. In this paper, a Simple Addictive Weighting (SAW) method and Profile Matching were proposed to solve employee selection problem. This research was conducted at UPT Career Development and Entrepreneurship Universitas Brawijaya Malang, using data collected from written test selection in 2019. The effectiveness of both methods is analyzed by means of confusion matrix. SAW method give Accuracy rate of 94.7%, Precision rate of 87.5%, Recall rate of 91.3% and F-measure rate of 89.4%. On the other hand, Profile Matching method obtained the Accuracy rate of 90.4.7%, Precision rate of 81.4%, Recall rate of 81.4% and F-measure rate of 81.4%. From these results, it can be concluded that both methods have a high accuracy value accompanied by a high precision value when used for the selection process. This system can also reduce the bias of the same data very well, as can be seen from the high Recall and F-measure rates.