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All Journal Pilar Teknologi : Jurnal Penelitian Ilmu-ilmu Teknik
Dewi Miftakhul Jannah
universitas merdeka madiun

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Pengembangan Platform Konseling Karier Mahasiswa Berbasis Profiling Digital dan Sistem Rekomendasi Menggunakan Machine Learning Amelia Dewi Pamudji; Tataz Sultan Elfandy; Dewi Miftakhul Jannah
JURNAL PILAR TEKNOLOGI Jurnal Ilmiah Ilmu Ilmu Teknik Vol. 11 No. 1 (2026): JURNAL PILAR TEKNOLOGI
Publisher : LPPM Universitas Merdeka Madiun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33319/piltek.v11i1.255

Abstract

The rapid development of digital technology and the growing need for personalized career guidance have driven the transformation of career counseling services in higher education. Many students still face difficulties in determining career paths that align with their interests, potential, and competencies. This issue is worsened by the limitations of conventional counseling services that are not yet data-driven. Therefore, this study develops a student career counseling platform based on digital profiling integrated with a recommendation system using Machine Learning. The research employed literature review and prototyping methodology. Student data (interests, academic performance, activities, and skills) were processed using Decision Tree and K-Nearest Neighbor (KNN) algorithms to generate relevant career-path recommendations. The results indicate that integrating digital profiling with a machine learning-based recommendation system enhances personalization, accuracy, and adaptability of career recommendations.
Co-Authors Amelia Dewi Pamudji Tataz Sultan Elfandy