Harun, Azhar Abiyu Rasendriya (2026) Penerapan Multi Objective Genetic Algorithm Berbasis Non-Dominated Sorting Algorithm-2 Untuk Penjadwalan Dokter Jaga IGD Di Rumah Sakit Islam Siti Hajar Sidoarjo. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Instalasi Gawat Darurat (IGD) merupakan lingkungan kerja dengan dinamika tinggi yang menuntut ketersediaan tenaga medis secara optimal selama 24 jam. Penjadwalan dokter jaga di unit ini sering kali menghadapi dilema kompleks (NP-Hard problem) karena harus menyeimbangkan berbagai aturan operasional yang ketat dengan kebutuhan manusiawi para dokter. (Safitri & Amalia, 2018) Metode manual yang konvensional cenderung memakan waktu, rentan terhadap human error, dan sering gagal menciptakan keadilan beban kerja, yang pada akhirnya dapat memicu kelelahan (burnout) tenaga medis. Penelitian ini mengusulkan pengembangan sistem penjadwalan otomatis menggunakan pendekatan Multi-Objective Genetic Algorithm (MOGA) dengan varian Non-dominated Sorting Genetic Algorithm II (NSGA-II). Berbeda dengan metode optimasi tunggal, pendekatan ini dirancang untuk menyelesaikan tiga fungsi tujuan (objective functions) yang saling bertentangan secara simultan: (1) Meminimalkan Hard Constraints Penalty demi menjamin kelayakan operasional, (2) Meminimalkan ketidaksesuaian preferensi dokter (Preference Penalty) untuk meningkatkan kepuasan kerja, dan (3) Meminimalkan variansi jam kerja (Fairness Penalty) agar beban kerja terdistribusi secara adil. Simulasi komputasional dilakukan menggunakan bahasa pemrograman Python dengan melibatkan data 13 dokter untuk periode penjadwalan satu bulan. Algoritma dilengkapi dengan mekanisme heuristic repair untuk menangani kendala spesifik seperti aturan wajib istirahat pasca-dinas malam (post-night shift rest). Hasil akhir penelitian ini berupa himpunan solusi Pareto Optimal, memberikan manajemen rumah sakit fleksibilitas untuk memilih jadwal terbaik berdasarkan trade-off antara efisiensi, kepuasan, dan keadilan.
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The Emergency Department (ED) is highly dynamic and requires optimal 24-hour staffing. Scheduling ED physicians is a complex combinatorial problem (NP-hard). It requires balancing strict operational protocols with the medical staff's well-being. Manual scheduling is time-consuming, error-prone, and often fails to distribute the workload equitably, leading to burnout. This study aims to develop an automated scheduling system using a Multi-Objective Genetic Algorithm (MOGA), specifically the Non-dominated Sorting Genetic Algorithm II (NSGA-II). The goal is to address three conflicting objectives: (1) Minimize Hard Constraints Penalty to ensure operational feasibility, (2) Minimize Preference Penalty to improve physician job satisfaction, and (3) Minimize Fairness Penalty (workload variance) to ensure equitable working hours. Computational simulations were conducted in Python. The model scheduled 13 physicians over the course of one month. The algorithm uses a heuristic repair mechanism to address constraints, such as mandatory post-night-shift rest. The final output provides Paretooptimal schedules, allowing the administration to choose the best option based on efficiency, satisfaction, and fairness.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Multi-Objective Genetic Algorithm, NSGA-II, Physician Scheduling, Emergency Department, Pareto Optimal, Workload Fairness, Penjadwalan Dokter, IGd |
| Subjects: | T Technology > T Technology (General) > T57.6 Operations research--Mathematics. Goal programming T Technology > T Technology (General) > T57.84 Heuristic algorithms. T Technology > T Technology (General) > T58.62 Decision support systems |
| Divisions: | Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Informatics Engineering > 55201-(S1) Undergraduate Thesis |
| Depositing User: | Azhar Abiyu Rasendriya Harun |
| Date Deposited: | 04 Nov 2026 08:28 |
| Last Modified: | 04 Nov 2026 08:28 |
| URI: | http://repository.its.ac.id/id/eprint/146026 |
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