Sistem Pendukung Keputusan Pemilihan (SPK) Jurusan pada Perguruan Tinggi Menggunakan Metode Simple Additive Weighting (SAW)

Abstract

Choosing a college major is a crucial decision that significantly impacts a student's future. This decision not only affects the academic path they will take but also their career and life in the future. A wrong choice of major can lead to a mismatch between a student's abilities and interests with the selected program, resulting in academic difficulties and financial waste. Therefore, it is essential for students to choose a major that aligns with their interests, talents, and other criteria such as tuition fees, accreditation, and career prospects after graduation. This study aims to assist students in the college major selection process by developing a Decision Support System (DSS) using the Simple Additive Weighting (SAW) method. The SAW method was chosen for its ability to rank alternatives based on the relevant criteria's weights, thus helping students make objective and efficient decisions. The research was conducted using the Rapid Application Development (RAD) approach, which includes four main stages: planning, design, coding, and testing. In the planning stage, system requirements were identified through interviews with students and document analysis. The design stage involved developing the SAW algorithm to provide recommendations for majors based on the weights of the selected criteria. The criteria used included tuition fees, program accreditation, career prospects, and alignment with the student's interests. After that, the coding stage implemented the system using an appropriate programming language. In the testing stage, the system was tested to ensure the recommendations provided were accurate and met expectations. The results showed that the system was effective in providing appropriate major recommendations through the ranking of relevant criteria. With this system, students can make their college major decision more objectively, quickly, and efficiently, thus reducing the risk of making wrong decisions.