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All Journal Jurnal Pengembangan Rekayasa dan Teknologi Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika
Sayekti, Annisa Nur Afifah Kusuma
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Mathematics Mechanical Engineering Transportation

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Penerapan Metode TOPSIS dengan Jarak Euclidean Terbobot Dalam Menentukan Kesesuaian Pekerjaan Untuk Lulusan Sarjana Sayekti, Annisa Nur Afifah Kusuma; Sulaiman, Raden
Jurnal Pengembangan Rekayasa dan Teknologi Vol. 8 No. 2 (2024): November (2024)
Publisher : Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/jprt.v8i2.11318

Abstract

Tingkat Pengangguran Terbuka (TPT) lulusan Diploma IV, S1, S2, dan S3 di Indonesia masih cukup tinggi, yaitu sebesar 5,52% pada Februari 2023. Kondisi ini menunjukkan perlunya solusi untuk membantu lulusan, khususnya sarjana sains komputer, mendapatkan pekerjaan yang sesuai. Penelitian ini bertujuan memberikan referensi pekerjaan di bidang teknologi yang sedang banyak dicari dengan menggunakan pendekatan Multi-Criteria Decision-Making (MCDM). Metode yang digunakan adalah TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) dan modifikasinya, Weighted Euclidean Distance TOPSIS (WED-TOPSIS), untuk merangking pekerjaan berdasarkan lima kriteria: keseimbangan kerja dan luar kerja, kompensasi dan keuntungan, peluang karir, penghasilan, serta tingkat kesulitan.
PENERAPAN METODE TOPSIS DENGAN JARAK EUCLIDEAN TERBOBOT DALAM MENENTUKAN KESESUAIAN PEKERJAAN UNTUK LULUSAN SARJANA Sayekti, Annisa Nur Afifah Kusuma; Sulaiman, Raden
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 6 No. 1 (2025): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v6i1.880

Abstract

The Open Unemployment Rate (TPT) for Diploma IV, Bachelor’s, Master’s, and Doctoral graduates in Indonesia remains high at 5.52% as of February 2023. This condition highlights the need for solutions to help graduates, particularly computer science bachelor's degree holders, secure suitable jobs. This study aims to provide job references in the technology sector that are in high demand using a Multi-Criteria Decision-Making (MCDM) approach. The method employed is the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and its modification, Weighted Euclidean Distance TOPSIS (WED-TOPSIS), to rank jobs based on five criteria: work-life balance, compensation, career opportunities, income, and level of difficulty. Ten technology-related jobs, such as Data Scientist, Machine Learning Engineer, and Software Engineer, were analyzed in this study. WED-TOPSIS was modified by adding weights to the positive and negative ideal solutions to reflect the importance of each criterion. The results indicate that WED-TOPSIS outperforms standard TOPSIS by providing rankings more aligned with the selected criteria priorities. This research is expected to serve as a guide for graduates in choosing appropriate jobs and help reduce unemployment among bachelor’s degree holders.
Co-Authors RADEN SULAIMAN