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All Journal Parameter: Journal of Statistics MATHunesa: Jurnal Ilmiah Matematika
Jefli, Fais
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Computer Science & IT Decision Sciences, Operations Research & Management Mathematics

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THE THE CONTRIBUTION OF VOCATIONAL EDUCATION TO PREDICTING YOUTH UNEMPLOYMENT IN SOUTHEAST SULAWESI: A MACHINE LEARNING APPROACH Jefli, Fais
Parameter: Journal of Statistics Vol. 5 No. 2 (2025)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2025.v5.i2.17882

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
DIGITALISASI SEBAGAI PENDORONG STATUS EKSPOR USAHA KEPULAUAN RIAU: PENDEKATAN REGRESI LOGISTIK BINER FIRTH Jefli, Fais; Puspita Sari, Maylani; Amanda, Rulistia; Vitto Siregar, Muhammad; Putri Laili Nur Alimah, Isnaini
MATHunesa: Jurnal Ilmiah Matematika Vol. 14 No. 1 (2026)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/mathunesa.v14n1.p307-315

Abstract

Usaha e-commerce merupakan kegiatan jual beli yang memanfaatkan perangkat digital, dan dalam era globalisasi saat ini menjadi solusi terhadap berbagai keterbatasan geografis, khususnya dalam menunjang aktivitas ekspor. Namun demikian, status ekspor usaha e-commerce di Kepulauan Riau masih tergolong rendah dibandingkan dengan provinsi lain, meskipun wilayah ini memiliki kedekatan geografis dengan negara tetangga seperti Malaysia dan Singapura. Berdasarkan kondisi tersebut, penelitian ini bertujuan untuk mengidentifikasi faktor-faktor yang memengaruhi status ekspor usaha e-commerce di Kepulauan Riau, dengan fokus pada aspek digitalisasi dan aspek kontrol usaha. Mengingat variabel respon bersifat biner dan terdapat ketidakseimbangan kelas (rare events), pendugaan parameter dilakukan menggunakan metode Penalized Maximum Likelihood Estimation (PMLE). Hasil uji parsial pada taraf signifikansi 10% menunjukkan bahwa variabel lama usaha beroperasi, penggunaan media sosial, dan pelatihan pemasaran digital berpengaruh signifikan dalam meningkatkan peluang ekspor. Dengan demikian, semakin lama usaha beroperasi, semakin optimal pemanfaatan media sosial, serta semakin sering mengikuti pelatihan pemasaran digital, maka kecenderungan usaha e-commerce untuk melakukan ekspor akan semakin tinggi.
Co-Authors Amanda, Rulistia Puspita Sari, Maylani Putri Laili Nur Alimah, Isnaini Vitto Siregar, Muhammad