Pengembangan Model Smart Career Link Berbasis Random Forest untuk Pemadanan Kompetensi Lulusan SMK dan Industri
DOI:
https://doi.org/10.30865/json.v8i1.10113Keywords:
Smart Career Link, Random Forest, Competency Matching, Kompetensi Lulusan, Sekolah Menengah KejuruanAbstract
Perubahan kebutuhan dunia kerja yang semakin dinamis menuntut lulusan Sekolah Menengah Kejuruan (SMK) memiliki kompetensi yang selaras dengan kebutuhan industri. Namun, pemadanan kompetensi lulusan dengan kebutuhan pekerjaan masih terkendala karena informasi kompetensi dan lowongan kerja belum terintegrasi secara optimal. Penelitian ini bertujuan mengembangkan model Smart Career Link berbasis Random Forest untuk melakukan pemadanan kompetensi lulusan SMK dengan kebutuhan industri dan menghasilkan rekomendasi pekerjaan yang relevan. Penelitian menggunakan pendekatan Research and Development (R&D), sedangkan Waterfall digunakan sebagai model pengembangan sistem perangkat lunak. Data diperoleh dari SMK Negeri 2 Kota Bima tahun 2025-2026, berupa profil kompetensi lulusan dan persyaratan kompetensi pekerjaan. Dari 330 pasangan potensial profil kompetensi dan lowongan pekerjaan, 200 pasangan yang memenuhi kriteria kelengkapan dan relevansi digunakan sebagai dataset. Setiap pasangan merepresentasikan satu unit pemadanan dan diberi label Sesuai atau Tidak Sesuai berdasarkan persyaratan pekerjaan yang diverifikasi oleh BKK, guru produktif, dan/atau mitra industri. Pemadanan mempertimbangkan bidang keahlian, kompetensi teknis, sertifikasi, dan pengalaman praktik kerja industri. Random Forest digunakan untuk klasifikasi kesesuaian. Stratified 5-Fold Cross-Validation menghasilkan accuracy 93,50±1,37%, precision 93,17±2,27%, recall 94,00±4,18%, dan F1-score 93,51±1,48%. Pengujian 40 data testing menghasilkan accuracy 92,50%. Black-box testing terhadap 11 fungsi utama menunjukkan seluruh fungsi berjalan sesuai kebutuhan.
References
[1] P. Rikala, G. Braun, M. Järvinen, J. Stahre, and R. Hämäläinen, “Understanding and measuring skill gaps in Industry 4.0—A review,” Technol. Forecast. Soc. Change, vol. 201, p. 123206, 2024.
[2] A. Bhoj, “Aligning Education with Industry: Evaluating Vocational Courses across Undergraduate, Graduate and Postgraduate Levels,” Dev. Res., p. 209, 2024.
[3] N. Paramitasari, K. Khoirunurrofik, B. R. Mahi, and D. Hartono, “Charting vocational education: impact of agglomeration economies on job–education mismatch in Indonesia,” Asia-Pacific J. Reg. Sci., vol. 8, no. 2, pp. 461–491, 2024.
[4] A. Botezat, C. Incaltarau, S. A. Diac, and A. C. Grosu, “Having your career path decided too early: the effects of high school track on education-occupation mismatch,” Int. J. Manpow., vol. 45, no. 6, pp. 1171–1190, 2024.
[5] R. W. Daryono, M. A. Ramadhan, N. Kholifah, F. D. Isnantyo, and M. Nurtanto, “An empirical study to evaluate the student competency of vocational education,” Int. J. Eval. Res. Educ., vol. 12, no. 2, pp. 1079–1086, 2023.
[6] G. Wang and Z. Wang, “Vocational education: a poor second choice? A comparison of the labour market outcomes of academic and vocational graduates in China,” Oxford Rev. Educ., vol. 49, no. 3, pp. 408–427, 2023.
[7] S. Rahmadhani and L. Suryati, “Vocational high school students’ competency needs to the world of work,” Mimb. Ilmu, vol. 27, no. 2, pp. 349–355, 2022.
[8] A. S. Lopes, I. Rebelo, R. Santos, R. Costa, and V. Ferreira, “Supply and demand matching of VET skills-a regional case study,” Cogent Educ., vol. 10, no. 1, p. 2200550, 2023.
[9] A. Müller, “Cooperation between colleges and companies: Vocational education, skill mismatches and China’s turnover problem,” China Q., vol. 260, pp. 986–1004, 2024.
[10] S. Gooptu, C. Bros, and S. R. Chowdhury, “Estimating skill mismatch in the Indian labour market: A regional dimension,” Glob. Bus. Rev., p. 09721509221146400, 2023.
[11] J. Mondolo, G. Pedrini, and M. Cucculelli, “Understanding the skill provision of the I4. 0 digital transformation: evidence from Italian companies,” Eurasian Bus. Rev., pp. 1–44, 2026.
[12] I. Bohashko and O. Bohashko, “Development of organisational competencies during transition and adaptation to industry 4.0.,” in ENVIRONMENT. TECHNOLOGY. RESOURCES. Proceedings of the International Scientific and Practical Conference, 2024, pp. 34–38.
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Jurnal Sistem Komputer dan Informatika (JSON)
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
This work is licensed under a Creative Commons Attribution 4.0 International License
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (Refer to The Effect of Open Access).
