Recommendation Systems for Online Learning Materials Using Cosine Similarity and Simple Additive Weighting

Abstract

This study focuses on searching for teaching materials in order to obtain relevant teaching material information appropriately for further use as material for recommendation of course material to students using the Cosine Similarity method and calculating weighting using the Simple Additive Weighting (SAW) method. With the SAW method, 3 criteria and weight values are determined for each attribute, followed by a ranking process. So that in the end the search results that are ranked in the order of similarity and most relevant can be displayed and then selected and used as recommendations in the student's e-learning learning system. From the results of the study, the Cosine Similarity and SAW methods have provided a fairly good/effective recommendation with an average precision of 0.7867 and a recall of 0.766 so that this method is appropriate to be placed in campus e-Learning