Implementasi Metode Simple Additive Weighting (SAW) pada Sistem Informasi Magang Mahasiswa Berbasis Web untuk Penilaian Akhir Magang

Abstract

The implementation of the student internship program at the Faculty of Computer Science, Universitas Singaperbangsa Karawang (Fasilkom UNSIKA) is currently hindered by a semi-conventional administrative system, decentralized academic document archiving, and vulnerability to human errors during the conversion score calculation process. This study aims to design and develop a web-based Student Internship Information System that specifically integrates a Decision Support System (DSS) function to digitalize the bureaucratic cycle while automating the internship final evaluation in an objective, transparent, and accurate manner. The software engineering applies the Waterfall development model and is constructed using a modern tech stack consisting of Next.js, React.js, Node.js, Sequelize ORM, and a MySQL database. To produce fair evaluation decisions, the platform implements the Simple Additive Weighting (SAW) algorithm within the backend system as a computational engine to execute benefit normalization and linear weighted summation of multi-source score components, aligned with the faculty's internship conversion Course Learning Outcomes (CPMK) criteria matrix. The result of this thesis research is a centralized digital platform that accommodates the administrative data needs of students, supervisors, examiners, and administrators. Through the implementation of the automated SAW algorithm, the system is proven reliable in streamlining the conventional grade recapitulation bureaucracy, eliminating human error risks, and presenting transparent score sheets along with precise evaluation ranking charts to enhance the faculty's academic management efficiency.