Employee Performance Evaluation Using RECA-based Weighting and RAWEC: Evidence from Textile Manufacturing
Evaluasi Kinerja Karyawan Menggunakan Pembobotan Berbasis RECA dan RAWEC: Studi Empiris pada Industri Manufaktur Tekstil
DOI:
https://doi.org/10.24002/jbi.v17i1.13709Keywords:
Employee Performance, Textile Industry, Multi-Criteria Decision, Objective Evaluation, Performance RankingAbstract
Employee performance evaluation in the textile industry production division still faces issues of subjectivity, limited indicators, and inconsistency in ranking that do not yet reflect the real contribution of employees. This study aims to assess employee performance using a multi-criteria decision-making approach by integrating the RECA method for determining objective criterion weights and the RAWEC method for generating performance rankings. Performance data is collected based on several key criteria, namely work productivity, production quality, timeliness, work discipline, and production error rates, which reflect the operational conditions in the textile manufacturing environment. The analysis results indicate that the applied approach clearly distinguishes employee performance and produces a stable ranking, with Gina taking first place with a final score of 0.483 and Citra with a score of 0.2933. These findings indicate that RECA and RAWEC support more reliable and data-driven managerial decisions in the textile industry.
Evaluasi kinerja karyawan di divisi produksi industri tekstil masih menghadapi masalah subjektivitas, keterbatasan indikator, dan ketidakkonsistenan pemeringkatan yang belum mencerminkan kontribusi nyata karyawan. Penelitian ini bertujuan untuk menilai kinerja karyawan menggunakan pendekatan pengambilan keputusan multi-kriteria dengan mengintegrasikan metode RECA untuk menentukan bobot kriteria objektif dan metode RAWEC untuk menghasilkan peringkat kinerja. Data kinerja dikumpulkan berdasarkan beberapa kriteria utama, yaitu produktivitas kerja, kualitas produksi, ketepatan waktu, disiplin kerja, dan tingkat kesalahan produksi, yang mencerminkan kondisi operasional pada lingkungan manufaktur tekstil. Hasil analisis menunjukkan bahwa pendekatan yang diterapkan mampu membedakan kinerja karyawan secara jelas dan menghasilkan pemeringkatan yang stabil, di mana Gina menempati peringkat pertama dengan nilai akhir 0.483 Citra dengan nilai 0,2933. Temuan ini menunjukkan RECA dan RAWEC mendukung keputusan manajerial yang lebih andal dan berbasis data di industri tekstil.
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