Decision Support System for Internship Acceptance at Digital Connection Using the Simple Additive Weighting Method

The internship program serves as a bridge for students into the professional world. At Digital Connection, the current manual selection process for internship candidates leads to inefficiency and potential errors. This study aims to implement a Decision Support System using the Simple Additive Weighting (SAW) method to improve the efficiency of the internship selection process. The SAW method is selected for its capability to provide accurate assessments based on predefined criteria and preference weights, as well as to rank the best alternatives. The system is developed as a web-based application with full access for HR (Admin), including tests as evaluation criteria. This research has resulted in the creation of a decision support system utilizing the Simple Additive Weighting (SAW) calculation method. System testing, conducted using black-box testing, shows that all primary functions and buttons of the system, such as adding, editing, deleting, searching, logging in, managing criteria and sub-criteria data, managing alternative data, calculating scores, exporting, and logging out, function properly and as expected. Furthermore, user testing with 6 criteria and 10 alternative input data points revealed the highest rank of 100% for Wahyu, followed by Noelino in second place with 76%, Hana in third place with 74%, and the lowest rank for Sanjaya with 58%. These results confirm that the calculation system operates effectively according to the researched method and provides clear ranking evaluations to assist HR (Admin) in determining the most suitable internship candidates. The system was implemented on a website using the waterfall model approach as the development method for the research system.