Implementation of Greedy Algorithm for National Selection of New Students at MAN Insan Cendekia OKI

Abstract

The National Selection of New Learners at MAN Insan Cendekia OKI is a process of selecting the best students based on certain criteria. This selection process requires an efficient method to ensure that the selected participants have qualities that match the school's standards. The Greedy Algorithm is one approach that can be used to solve optimization problems such as learner selection. This algorithm works by taking locally optimal decisions at each stage in the hope of getting an overall optimal solution. This research aims to implement the Greedy algorithm in the Selection of New Learners process at MAN Insan Cendekia OKI. In its application, the Greedy algorithm will be used to select participants based on criteria such as academic scores, non-academic achievements, and other factors deemed relevant by the school. The results of this study show that the Greedy algorithm can be applied well in the selection of students and is able to improve the efficiency of the selection process. However, there are some limitations that need to be considered, especially in terms of dynamic selection criteria and the possibility of non-optimal solutions in certain cases. Thus, the Greedy algorithm provides an interesting alternative in solving selection problems while still considering further development so that the results obtained are more optimal.