Optimizing Lecturer Selection with the Simple Additive Weighting (SAW) Method: A Decision-Making Perspective

Decision support systems represent the practical application of various decision-making theories derived from disciplines such as operations research and management science. Traditionally, solving complex problems required manual iterative calculations or relied on identifying minimum, maximum, or optimal values through time-consuming processes. However, advancements in computing technology have significantly reduced the time needed to address such problems efficiently. This study employs the Simple Additive Weighting (SAW) method to optimize the selection process of permanent lecturers, providing a systematic and objective framework to identify the most suitable candidates. By leveraging the SAW method, the decision-making process becomes more transparent, accurate, and aligned with institutional goals, ultimately enhancing the quality and fairness of lecturer recruitment.