Content-based filtering using cosine similarity algorithm for alternative selection on training programs

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Muhammad Falah Abdurrafi
Dewi Handayani Untari Ningsih

Abstract

The large selection of training programs provided by the Ministry of Manpower of the Republic of Indonesia makes it difficult for prospective trainees to choose a training program that suits their interests and needs. The purpose of this research is to support the selection process so that an appropriate method is needed to recommend the selection of training programs that match the interests and needs of users. One of the selection methods that can be used is the Content-Based Filtering method with similarity measurement using Cosine Similarity. The content-based filtering method is a content-based filtering method, which recommends training programs based on the suitability between the description of the training program and the interests of prospective trainees using the cosine similarity distance measurement. The test results using the Content-Based Filtering method were able to achieve an average precision value of 88%, indicating the ability of the system to provide training program recommendations that are very relevant and in accordance with the interests and needs of the trainees.

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[1]
M. F. Abdurrafi and D. H. U. Ningsih, “Content-based filtering using cosine similarity algorithm for alternative selection on training programs”, J. Soft Comput. Explor., vol. 4, no. 4, pp. 204-212, Dec. 2023.
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