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All Journal RABIT: Jurnal Teknologi dan Sistem Informasi Univrab
Rizal Rio Andrian
Universitas Mercu Buana Yogyakarta
Computer Science & IT Engineering

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SISTEM PENDUKUNG KEPUTUSAN PENILAIAN KESIAPAN PSIKOLOGIS CALON PEKERJA MIGRAN INDONESIA DENGAN AHP DAN TOPSIS: SISTEM PENDUKUNG KEPUTUSAN PENILAIAN KESIAPAN PSIKOLOGIS CALON PEKERJA MIGRAN INDONESIA DENGAN AHP DAN TOPSIS Rizal Rio Andrian; Agus Sidiq Purnomo
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.7978

Abstract

The selection of psychological readiness for Indonesian Migrant Worker Candidates (CPMI) at placement institutions often faces subjectivity constraints that risk mental unpreparedness in destination countries. This study aims to implement a Decision Support System (DSS) using a hybrid Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method to enhance selection objectivity. The system development methodology follows the Turban model encompassing intelligence, design, choice, and implementation phases. The research employs eight psychological criteria involving three experts for criteria weighting and 40 alternative CPMI candidates for ranking. AHP weighting results indicate Work Motivation (0.206) and Discipline (0.203) as the most dominant parameters with validated Consistency Ratio ≤ 0.1. TOPSIS implementation produces preference values ranging from 0.134 to 0.882, classified into Ready, Sufficiently Ready, and Needs Strengthening categories. Sensitivity analysis demonstrates that the hybrid model aggregation is more robust indicated by the high stability of top-ranking candidates compared to individual expert preference scenarios and Equal Weight methods. In conclusion, this system successfully transforms qualitative assessments into transparent and accurate quantitative indicators to support managerial decision-making in the CPMI selection process.
Co-Authors Sidiq Purnomo, Agus