Nurmaya Nurmaya, Herika Hayurani, Muhammad Al Ziqri, Nova Eka Diana, Lisa Wiyartanti


Surgical schedule changes, caused by uncertainty case on the day of operation, can decrease the hospital’s service quality. Resilience Concept algorithm produces the risk value for schedule modification caused by the uncertainty case. However, this algorithm only managed the delay of elective surgery in previous research. Therefore, this study applies the resilience concept algorithm in handling the emergency case, and the shift of elective surgery into earlier than its current schedule. Resilience algorithm’s performance is compared to Rule-Based algorithm in managing the surgery’s schedule for uncertainty case. There are 20 test scenarios, consisting of 12 scenarios for elective surgery schedule changes and 8 scenarios for emergency case, that were given trial to the algorithms. Both of the algorithms 100% succeeded passing through all the scenarios. Yet, both of the algorithms could not give the priority schedule changes based on the risk level. Resilience algorithm could not give the priority based on the risk level of value caused by the imperfection of the resources delay calculation (Tn).

Keywords: Surgical schedule, Resilience Concept, Rule-Based, Uncertainty Case, Emergency Case


Perubahan jadwal operasi akibat kejadian tidak terduga (uncertainty case) di hari-H operasi dapat menurunkan kualitas layanan rumah sakit. Algoritma Resilience Concept menghasilkan nilai resiko untuk setiap perubahan jadwal operasi yang terjadi akibat uncertainty case. Namun, algoritma ini hanya mengelola perubahan jadwal akibat keterlambatan penyelesaian operasi elektif, yang merupakan salah satu uncertainty case, pada penelitian sebelumnya. Oleh karena itu, penelitian ini menerapkan algoritma resilience concept dalam menangani kasus gawat darurat (emergency case), dan perubahan waktu pelaksanaan operasi elektif menjadi lebih awal. Kinerja algoritma resilience concept dibandingkan dengan algoritma rule-based dalam mengelola jadwal operasi untuk uncertainty case. Terdapat 20 skenario pengujian diujicobakan kepada kedua algoritma, yang terdiri dari 12 skenario pengujian perubahan jadwal operasi elektif dan 8 skenario emergency case . Kedua algoritma 100% berhasil mengeksekusi semua skenario pengujian. Akan tetapi, keduanya belum dapat memberikan prioritas perubahan jadwal berdasarkan tingkatan resiko. Ketidakoptimalan perhitungan waktu keterlambatan sumber daya (Tn) menjadi penyebab algoritma Resilience belum dapat memberikan prioritas solusi berdasarkan nilai resiko yang dihasilkan.

Kata Kunci: Jadwal Operasi, Resilience Concept, Rule-Based, Uncertainty Case, Emergency Case.


Surgical schedule; Resilience Concept; Rule-Based; Uncertainty Case; Emergency Case

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