Recommendation System of Information Technology Jobs using Collaborative Filtering Method Based on LinkedIn Skills Endorsement

Latifah Diah Kumalasari, Ajib Susanto,



Abstract

Students who are graduated from Informatics Engineering have wide employment opportunities in the information technology work field, such as database administrator, data scientist, UI designer, IT project manager, network engineer, system analyst, software engineer and UX designer. Each job in Information Technology field has different skill requirement for the interest of work field. Therefore, IT skill classification is needed to find out the suitable career recommendation for Informatics Engineering students. Data from IT professionals which are obtained from LinkedIn account of IT professionals will be processed as reference for students. Data are processed using K-Means Clustering algorithm to find out how is feasible IT professionals data are used as a reference. Then, Collaborative Filtering method by the K-NN algorithm is used to determine classification based on the proximity between student skills and information technology job field. The output is recommendation of information technology job field which are generated from calculate of IT student skills. Result has been tested by testing one of user that has been labeled software engineer produce a recommendation output as a software engineer.


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Keywords

Classification, Clustering, Collaborative Filtering, IT Career Field Recommendation, K-Means, K-Nearest Neighbor

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DOI: https://doi.org/10.24167/sisforma.v6i2.2240

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