Optimasi Penjadwalan Perawat Menggunakan Fuzzy Goal Programming: Studi Kasus di UGD RSUD Kota Semarang
Date
2026Author
Wigawijayanti
Supriyo, Prapto Tri
Silalahi, Bib Paruhum
Metadata
Show full item recordAbstract
Penjadwalan perawat memiliki peran penting dalam mendukung efektivitas
operasional rumah sakit dan kualitas pelayanan kesehatan. Penyusunan jadwal
perawat yang masih dilakukan secara manual sering kali kurang efisien dan rentan
terhadap kesalahan, terutama ketika melibatkan banyak perawat dan berbagai
aturan kerja. Penelitian ini bertujuan membangun model penjadwalan perawat di
Unit Gawat Darurat RSUD Kota Semarang menggunakan Fuzzy Goal
Programming (FGP) dengan bantuan perangkat lunak LINGO 21.0 serta
membandingkan hasilnya dengan Goal Programming (GP). Model yang
dikembangkan mempertimbangkan berbagai kendala dan preferensi kerja perawat,
meliputi jumlah minimum shift pagi, siang, dan malam, pemerataan jumlah shift,
serta pemberian libur di akhir pekan. Hasil penelitian menunjukkan bahwa model
FGP yang dibangun menghasilkan solusi penjadwalan dengan distribusi beban
kerja yang lebih merata dibandingkan model GP. Nurse scheduling plays a crucial role in supporting the operational
effectiveness of hospitals and the quality of healthcare services. Scheduling that is
performed manually is often inefficient and prone to errors, particularly when it
involves a large number of nurses and various work regulations. This study aims to
develop a nurse scheduling model for the Emergency Department of Semarang
Regional Public Hospital using the Fuzzy Goal Programming (FGP) with the
assistance of LINGO 21.0 software and to compare the results with those obtained
using the Goal Programming (GP). The proposed model incorporates various
scheduling constraints and nurses' work preferences, including the minimum
number of morning, afternoon, and night shifts, equitable distribution of shifts, and
weekend day-off assignments. The results indicate that the developed FGP model
produces a nurse scheduling solution with a more balanced workload distribution
than the GP model.
Collections
- UF - Mathematics [164]

