Simulasi Agent-Based dalam Prediksi Turnover dan Strategi Retensi Karyawan
DOI:
https://doi.org/10.47134/jacis.v6i1.157Keywords:
Manajemen Sumber Daya Manusia (SDM), Simulasi Berbasis Agen, Turnover Karyawan, Strategi Retensi, Pengembangan KarierAbstract
Tingginya tingkat perputaran (turnover) karyawan menimbulkan tantangan operasional yang signifikan pada industri padat karya seperti peternakan ayam. Penelitian ini menerapkan metode Agent-Based Modeling (ABM) menggunakan sistem ERP berbasis spreadsheet untuk memprediksi dinamika turnover dan mengevaluasi efektivitas strategi retensi. Menggunakan data historis Human Capital, kami mensimulasikan perilaku 200 agen heterogen selama periode 24 bulan di bawah tiga skenario eksperimental: Baseline (Kontrol), Bonus Finansial, dan Jenjang Karir (Career pathing). Simulasi menunjukkan bahwa penerapan Career pathing menghasilkan penurunan tingkat turnover tahunan dari 70,65% (skenario kontrol) menjadi 60,87%, yaitu berkurang sebesar 9,78 poin persentase, sehingga menjadikannya intervensi paling efektif secara operasional. Temuan ini sejalan dengan literatur yang menyatakan bahwa pengembangan profesional mengurangi intensi keluar karyawan. Namun, analisis biaya-manfaat mengungkapkan sebuah paradoks: penerapan Career pathing secara universal menyebabkan defisit finansial yang masif akibat tingginya biaya retensi, sedangkan skenario Kontrol justru paling efisien secara finansial meskipun tingkat atrisinya tinggi. Studi ini menyimpulkan bahwa meskipun insentif non-finansial efektif menstabilkan tenaga kerja, penerapannya harus ditargetkan secara selektif menggunakan pendekatan berbasis data untuk menjamin kelayakan finansial
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