Sistem Rekomendasi Pekerjaan di bidang IT Menggunakan Algoritma Content-Based Filtering

Authors

  • Crismastiana Koloman Universitas Katolik Widya Mandira
  • Raihan Maulana Universitas Negeri Medan
  • Raisya Dwi Zahra Putri Universitas Negeri Medan
  • Wahyu Abadi Harahap Universitas Negeri Medan

DOI:

https://doi.org/10.55606/jcsrpolitama.v1i6.2992

Keywords:

Recommendation System, Content-Based Filtering, Career

Abstract

Rapid growth in the Information Technology (IT) industry has created an abundance of career opportunities, but job seekers often face difficulty in finding jobs that match their background and skills. To overcome this challenge, this research presents a “Job Recommendation System” that focuses on the IT industry. The method used in this research is "Content-Based Filtering," which allows the system to recommend jobs based on similarities between the skills possessed by the user and the available job descriptions. The system allows users to enter their skills, and based on these skills, analyzes the description jobs to recommend suitable jobs. Apart from providing job recommendations, this method also helps users to identify skill areas that need improvement. The research results show that the content-based filtering method is a powerful approach for providing relevant and effective job recommendations in the IT industry. This method provides great benefits to job seekers, helping them find job opportunities that suit their background and skills. In addition, this method has the potential to be applied in various applications in various industries.

References

Ardiansyah, R., Ari Bianto, M., & Saputra, B. D. (2023). Sistem Rekomendasi Buku Perpustakaan Sekolah menggunakan Metode Content-Based Filtering. Jurnal CoSciTech (Computer Science and Information Technology), 4(2), 510–518. https://doi.org/10.37859/coscitech.v4i2.5131

Ayu, D., Safitri, N., Helilintar, R., & Wahyuniar, L. S. (n.d.). Sistem Rekomendasi Skincare Menggunakan Metode Content-Based Filtering dan Algoritma Apriori.

Darmayanti, L., Barus, P. C., & Kartini. (2020). 4653-Article Text-8476-1-10-20221205 (2). Jurnal Edukasi Nonformal, 3(2), 197–206.

Deviacita, D., #1, A., Sasty, H., #2, P., Muhardi, H., Profesor, J., Nawawi, D. H. H., Laut, B., Tenggara, P., Pontianak, K., & Barat, K. (2019). Implementasi Web Scraping untuk Pengambilan Data pada Situs Marketplace. 7(4).

Fajriansyah, M., Adikara, P. P., & Widodo, A. W. (2021). Sistem Rekomendasi Film Menggunakan Content Based Filtering (Vol. 5, Issue 6). http://j-ptiik.ub.ac.id

Ferio, G., Intan, R., & Rostianingsih, S. (n.d.). Sistem Rekomendasi Mata Kuliah Pilihan Menggunakan Metode User Based Collaborative Filtering Berbasis Algoritma Adjusted Cosine Similarity.

Habibi, R., & Dzihan Albanna, M. (2022a). ANALISIS SISTEM REKOMENDASI PADA JOB RECOMMENDATION BERDASARKAN PROFIL LINKEDIN MENGGUNAKAN COSINE SIMILARITY. In Jurnal Teknik Informatika (Vol. 14, Issue 3).

Habibi, R., & Dzihan Albanna, M. (2022b). ANALISIS SISTEM REKOMENDASI PADA JOB RECOMMENDATION BERDASARKAN PROFIL LINKEDIN MENGGUNAKAN COSINE SIMILARITY. In Jurnal Teknik Informatika (Vol. 14, Issue 3).

Hartarto Muliadi, K., & Citra Lestari, C. (2019). Rancang Bangun Sistem Rekomendasi Tempat Makan Menggunakan Algoritma Typicality Based Collaborative Filtering Engineering of a Dining Place Recommendation System Using Typicality Based Collaborative Filtering Algorithm (Vol. 18, Issue 4).

Huda, A. A., Fajarudin, R., & Hadinegoro, A. (2022). Sistem Rekomendasi Content-based Filtering Menggunakan TF-IDF Vector Similarity Untuk Rekomendasi Artikel Berita. Building of Informatics, Technology and Science (BITS), 4(3). https://doi.org/10.47065/bits.v4i3.2511

Miquido. (2020, July 28). We know what you like! Perks of recommendation systems in business. Miquido.Com.

MULYAWAN SKom, B., & SUTRISNO SSi, T. (n.d.). Jurnal Ilmu Komputer dan Sistem Informasi PEMBUATAN APLIKASI E-COMMERCE BERBASIS WEB DENGAN FITUR REKOMENDASI MENGGUNAKAN METODE CONTENT-BASED FILTERING.

Nastiti, P. (2019). Penerapan Metode Content Based Filtering Dalam Implementasi Sistem Rekomendasi Tanaman Pangan. Teknika, 8(1), 1–10. https://doi.org/10.34148/teknika.v8i1.139

Ningtyas, D. F., & Setiyawati, N. (2021). Implementasi Flask Framework pada Pembangunan Aplikasi Purchasing Approval Request. Jurnal Janitra Informatika Dan Sistem Informasi, 1(1), 19–34. https://doi.org/10.25008/janitra.v1i1.120

Nugroho, F., & Rahayu, M. I. (2020). SISTEM REKOMENDASI PRODUK UKM DI KOTA BANDUNG MENGGUNAKAN ALGORITMA COLLABORATIVE FILTERING. 2(3), 23–31.

Putri, D. A., Pramesti, D., I, D., & Santiyasa, W. (2022). Penerapan Metode Content-Based Filtering dalam Sistem Rekomendasi Video Game. In JNATIA (Vol. 1, Issue 1).

Raharjo, P. N., Handojo, A., & Juwiantho, H. (n.d.-a). Sistem Rekomendasi Content Based Filtering Pekerjaan dan Tenaga Kerja Potensial menggunakan Cosine Similarity.

Raharjo, P. N., Handojo, A., & Juwiantho, H. (n.d.-b). Sistem Rekomendasi Content Based Filtering Pekerjaan dan Tenaga Kerja Potensial menggunakan Cosine Similarity.

Ro’uf, A., Pranoto, Y. M., & Setyati, D. E. (n.d.). Sistem Rekomendasi Pekerjaan Menggunakan Content Based Similarity. https://www.bps.go.id/

Roy, A. (2020, July 29). Introduction To Recommender Systems- 1: Content-Based Filtering And Collaborative Filtering. Towardsdatascience.Com.

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Published

2023-12-01

How to Cite

Crismastiana Koloman, Raihan Maulana, Raisya Dwi Zahra Putri, & Wahyu Abadi Harahap. (2023). Sistem Rekomendasi Pekerjaan di bidang IT Menggunakan Algoritma Content-Based Filtering. Journal of Creative Student Research, 1(6), 78–88. https://doi.org/10.55606/jcsrpolitama.v1i6.2992

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