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Abstract
Youth unemployment remains a major issue in Indonesia, including in Southeast Sulawesi Province. Although the overall open unemployment rate in this province is relatively low, the unemployment rate among young people is still quite high. One contributing factor is the mismatch between educational outcomes and labor market needs, especially for those entering the workforce for the first time. In this context, vocational education is expected to enhance youth employability. Therefore, this study aims to classify youth employment status and identify the predictor that contribute most to the prediction results, particularly vocational education, using SHapley Additive exPlanations (SHAP) values to interpret model decisions. Several machine learning classification methods were evaluated, including naïve Bayes and random forest, with logistic regression used as the baseline comparison model. The findings indicate that the random forest model provides the best classification performance. Based on the analysis, vocational education and age group are the most influential predictors in classifying youth employment status in Southeast Sulawesi Province. Thus, vocational education serves as a key predictor that enhances the model’s ability to classify employment status and is associated with a higher model-predicted probability of being employed
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References
- Ardhana, A. Y. A., Syazeedah, H. N. U., Fitriyaningrum, R. I., & Gunawan, A. (2025). Analisis ketidaksesuaian antara pendidikan dengan kebutuhan dunia kerja di Indonesia. Kompeten: Jurnal Ilmiah Ekonomi dan Bisnis, 3(4), 1020–1026.
- Adriyanto, A., Prasetyo, D., & Khodijah, R. (2020). Angkatan Kerja dan Faktor yang Mempengaruhi Pengangguran. Jurnal Ilmu Ekonomi & Sosial Unmus, 11(2). https://doi.org/10.35724/jies.v11i2.2965
- Alam, S. (2016). Tingkat Pendidikan dan Pengangguran di Indonesia (Telaah Serapan Tenaga Kerja SMA/SMK dan Sarjana). Jurnal Ilmiah Bongaya, 1(1), 250–257. https://ojs.stiem-bongaya.ac.id/JIB/article/view/19
- Alharis, F., & Yuniasih, A. (2022). Determinan Pengangguran Usia Muda Terdidik di Provinsi Banten Tahun 2020. Seminar Nasional Official Statistics, 2022, 53–62. https://doi.org/10.34123/semnasoffstat.v2022i1.1153
- Badan Pusat Statistik. (2024a). Tingkat pengangguran terbuka berdasarkan kelompok umur. https://www.bps.go.id/id/statistics-table/2/MTE4MCMy/tingkat-pengangguran-terbuka-berdasarkan-kelompok-umur.html
- Badan Pusat Statistik. (2024b). Statistik Indonesia 2024.
- Febryanna, S. (2022). Pola Karakteristik NEET (Not In Employment, Education, Or Training) Dan Pengaruh Pengetahuan Pemuda Tentang Program Kartu Prakerja Terhadap Status NEET Di Masa Pandemi. Seminar Nasional Official Statistics, 2022(1), 11–20. https://doi.org/10.34123/semnasoffstat.v2022i1.1113
- Ihfa, R., & Harsanti, T. (2021). Komparasi Teknik Resampling pada Pemodelan Regresi Logistik Biner. Seminar Nasional Official Statistics, 2020(1). https://doi.org/10.34123/semnasoffstat.v2020i1.540
- James, G., Witten, D., Hastie, T., & Tibshirani, R. (2021). An Introduction to Statistical Learning (2nd ed.). Springer New York, NY. https://doi.org/https://doi.org/10.1007/978-1-0716-1418-1
- Maulana, A., & Suryaningrum, N. (2023). Pendidikan vokasi, pelatihan dan pengangguran usia muda di Indonesia pada masa pandemi Covid-19. Jurnal Kependudukan Indonesia, 18(1), 93–108. https://doi.org/10.55981/jki.2023.1697
- Mitsi, D. (2023). Unemployment and Economic Growth: An In-depth Analysis. International Journal of Science and Management Studies. https://doi.org/10.51386/25815946/ijsms-v6i4p115
- Ohara, E., Harto, S. P., & Maruanaya, R. F. (2020). Policy Shift to Reduce Unemployment of Vocational School Graduates in Indonesia (A National Study). Jurnal Pendidikan Teknologi Dan Kejuruan, 26(2), 129–139. https://doi.org/10.21831/jptk.v26i2.33144
- Pemerintah Republik Indonesia. (2022). Peraturan Presiden Republik Indonesia Nomor 68 Tahun 2022 tentang Revitalisasi Pendidikan Vokasi dan Pelatihan Vokasi. Lembaran Negara Republik Indonesia Tahun 2022 Nomor 108.
- Pramesti, K. D., Meisya, N. I., & Amrillah, R. (2024). Relevansi Lulusan Perguruan Tinggi dengan Dunia Kerja. An Najah (Jurnal Pendidikann Islam Dan Sosial Keagamaan), 3(4), 236–243. https://journal.nabest.id/index.php/annajah
- Rodríguez-Pérez, R., & Bajorath, J. (2020). Interpretation of machine learning models using shapley values: application to compound potency and multi-target activity predictions. Journal of Computer-Aided Molecular Design, 34. https://doi.org/10.1007/s10822-020-00314-0
- Sari, R., Kharis Al Basyar, A., Rahman, A., & Wardoyo, S. (2024). Edukatif: Jurnal Ilmu Pendidikan Peran Pendidikan Vokasi dalam Meningkatkan Keterampilan Kerja di Era Industri 4.0. Jurnal Ilmu Pendidikan, 6. https://doi.org/10.31004/edukatif.v6i6.7849
- Subiyantoro, H., Tarziraf, A., & Asmara, A. Q. (2023, June). The Role of Vocational Education as the Key to Economic Development in Indonesia. Proceedings of the 3rd Multidisciplinary International Conference. https://doi.org/10.4108/eai.28-10-2023.2341745
- Yanindah, A. (2021). An insight into Youth Unemployment in Indonesia. Proceedings of The International Conference on Data Science and Official Statistics, 2021(1), 666–682. https://doi.org/10.34123/icdsos.v2021i1.229
- Yoana, Ilmiawan, A., & Rumayya, and. (2024). The role of vocational education on unemployment in Indonesia. Cogent Education, 11(1), 2340858. https://doi.org/10.1080/2331186X.2024.2340858
- World Bank. (2025). Unemployment, total (% of total labor force) (national estimate) [SL.UEM.TOTL.NE.ZS]. World Development Indicators. https://databank.worldbank.org/metadataglossary/world-development-indicators/series/SL.UEM.TOTL.NE.ZS