RANCANG BANGUN APLIKASI KURSUS ONLINE BERBASIS WEB DENGAN SISTEM REKOMENDASI METODE CONTENT-BASED FILTERING

Abstract

The Institute for Courses and Training is a non-formal education that provides various special training to educate students' skills. However, there are things that often become obstacles for prospective students, namely being confused about choosing courses according to their preferences. Therefore, the purpose of this research is to design an online course application with a recommendation system for the Content-based Filtering method. In addition, this research also applies the cosine similarity algorithm to determine courses that are similar to the course history that has been accessed by the user. The dataset used to run the recommendation system algorithm was taken from the Kaggle website entitled “Udemy Course” with a total of 3,682 records. The final result of this research is an online course application that can provide course recommendations based on the highest similarity value from the cosine similarity algorithm.

Keywords: Unsupervised Learning, Content-based Filtering, System Recommender, Machine Learning

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Published
2022-01-10
How to Cite
[1]
Y. Christian and K. Kelvin, “RANCANG BANGUN APLIKASI KURSUS ONLINE BERBASIS WEB DENGAN SISTEM REKOMENDASI METODE CONTENT-BASED FILTERING”, rabit, vol. 7, no. 1, pp. 23-36, Jan. 2022.
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Articles
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