Main Article Content

Abstract

Preparing a strong portfolio is a crucial aspect for students in entering the workforce, one of which can be achieved through participation in various competitions. However, selecting competitions that align with student competencies remains a challenge due to the abundance of competition information, diversity in student interests and abilities, and limitations in budget, time, and resources. This study develops a recommendation system based on a Hybrid Recommendation System designed to map student competencies to relevant competition types. The system integrates the Naive Bayes method to classify student competencies and Item-Based Collaborative Filtering to calculate similarities between competition types based on other users’ preferences. The system is developed incrementally using the waterfall approach, including the stages of planning, analysis, design, implementation, and testing. The model follows standard machine learning workflows, comprising data collection, exploration and preprocessing, model building, performance evaluation, and method integration. The research data includes student profiles, competencies, and competition preferences collected through surveys and internal databases. Evaluation results indicate that the system successfully provides relevant competition recommendations with an accuracy rate of 70%. These results demonstrate the system’s contribution in assisting students to select competitions that match their competencies, presented in a user-friendly web-based application.

Keywords

Item-Based Collaborative Filtering Naive Bayes Student Competency Mapping

Article Details

Author Biographies

Dini Nurmalasari, Politeknik Caltex Riau

Teknologi Rekayasa Komputer Politeknik Caltex Riau

Mardhiah Fadhli, Politeknik Caltex Riau

Teknologi Rekayasa Komputer Politeknik Caltex Riau

Yuli Fitrisia, Politeknik Caltex Riau

Teknologi Rekayasa Komputer Politeknik Caltex Riau

Heri R Yuliantoro, Politeknik Caltex Riau

Akuntansi Perpajakan Politeknik Caltex Riau
How to Cite
Nurmalasari, D., Fadhli, M., Yuli Fitrisia, Y. F., & Yuliantoro, H. R. (2025). INTEGRASI NAIVE BAYES DAN ITEM-BASED COLLABORATIVE FILTERING DALAM SISTEM PEMETAAN KOMPETENSI MAHASISWA. Jurnal Komputer Terapan, 11(1), 16–28. https://doi.org/10.35143/jkt.v11i1.6612

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