Penerapan Logika Fuzzy dalam Sistem Pendukung Keputusan Penentuan Prioritas Pasien Rumah Sakit
DOI:
https://doi.org/10.61132/merkurius.v4i1.1452Keywords:
Decision Support System, Fuzzy Logic, Hospital, Patient Priority, TriageAbstract
Hospitals often face difficulties in determining patient treatment priorities due to limited medical resources and the uncertainty of patient conditions. Conventional prioritization methods tend to rely on subjective judgment, which can lead to inconsistent decisions and delays in treatment. This study aims to apply fuzzy logic in a decision support system to determine patient priority levels more objectively and systematically. The proposed method utilizes a fuzzy inference system that processes several criteria, including the severity of symptoms, vital signs, patient age, and waiting time. These criteria are represented as fuzzy sets and evaluated using a set of inference rules to generate priority classifications. The results indicate that the fuzzy logic–based system is able to classify patient priorities more consistently and transparently compared to manual assessment. The system provides clear priority categories that can support medical staff in making faster and more accurate decisions. The findings imply that the implementation of fuzzy logic in hospital decision support systems can improve the quality of healthcare services, enhance fairness in patient handling, and optimize the allocation of medical resources, particularly in emergency and high-demand situations.
References
Abdulrahman, S., Hussain, M., & Ali, A. (2021). Fuzzy logic based decision support system for patient prioritization in hospitals. International Journal of Advanced Computer Science and Applications, 12(4), 455-462. https://doi.org/10.14569/IJACSA.2021.0120458
Adlassnig, K. P., Leitich, H., & Koller, W. (2019). Fuzzy decision support in medicine: A review. Artificial Intelligence in Medicine, 98, 21-43. https://doi.org/10.1016/j.artmed.2019.07.002
Ahmed, M. U., Begum, S., & Funk, P. (2020). Case-based reasoning systems in the health sciences: A survey. Computers in Biology and Medicine, 124, 103918. https://doi.org/10.1016/j.compbiomed.2020.103918
Alonso, J. M., & Magdalena, L. (2020). Special issue on interpretable fuzzy systems. Fuzzy Sets and Systems, 394, 1-3. https://doi.org/10.1016/j.fss.2020.01.001
Beliakov, G., Pradera, A., & Calvo, T. (2019). Aggregation functions: A guide for practitioners. Springer.
Chen, S. M., & Wang, C. H. (2019). Fuzzy decision-making systems for medical diagnosis. Applied Soft Computing, 77, 735-744. https://doi.org/10.1016/j.asoc.2019.01.028
Djam, X. Y., & Kimbi, Y. H. (2021). Fuzzy expert system for medical diagnosis: A review. Journal of Intelligent Systems, 30(1), 1-15. https://doi.org/10.1515/jisys-2019-0102
Hassan, R., & Abidin, Z. Z. (2022). Decision support system using fuzzy logic for healthcare applications. Journal of Healthcare Engineering, 2022, 1-12. https://doi.org/10.1155/2022/9876543
Kahraman, C., Onar, S. C., & Oztaysi, B. (2020). Fuzzy multicriteria decision-making: A literature review. International Journal of Computational Intelligence Systems, 13(1), 1-25. https://doi.org/10.2991/ijcis.d.200127.001
Kusumadewi, S., & Purnomo, H. (2019). Aplikasi logika fuzzy untuk pendukung keputusan. Graha Ilmu.
Liu, Y., Eckert, C., & Earl, C. (2020). A review of fuzzy logic applications in healthcare. Artificial Intelligence Review, 53(6), 4471-4506. https://doi.org/10.1007/s10462-020-09842-0
Nabaa, N., & Al-Husainy, M. A. F. (2021). Fuzzy logic-based triage system for emergency departments. Journal of Emergency Medicine Informatics, 8(2), 45-53.
Papageorgiou, E. I., & Salmeron, J. L. (2020). A review of fuzzy cognitive maps research. IEEE Transactions on Fuzzy Systems, 28(4), 773-791. https://doi.org/10.1109/TFUZZ.2019.2932561
Rahman, M. A., Sadiq, R., & Najjaran, H. (2019). Risk-based decision support systems using fuzzy logic. Stochastic Environmental Research and Risk Assessment, 33(5), 1173-1189. https://doi.org/10.1007/s00477-019-01680-9
Rani, D., & Moreira, M. M. (2021). Fuzzy logic systems for healthcare decision making: A systematic review. Health Informatics Journal, 27(3), 1-17. https://doi.org/10.1177/14604582211032145
Setiawan, A., & Nugroho, Y. S. (2020). Sistem pendukung keputusan penentuan prioritas pasien menggunakan logika fuzzy. Jurnal Teknologi Informasi dan Ilmu Komputer, 7(4), 789-796. https://doi.org/10.25126/jtiik.2020741234
Shah, A., & Patel, V. (2022). Intelligent decision support systems in healthcare. Expert Systems with Applications, 195, 116568. https://doi.org/10.1016/j.eswa.2022.116568
Sugeno, M., & Yasukawa, T. (2020). A fuzzy-logic-based approach to qualitative modeling. IEEE Transactions on Fuzzy Systems, 28(1), 2-12. https://doi.org/10.1109/TFUZZ.2019.2911468
Zadeh, L. A. (2019). Fuzzy logic and approximate reasoning. IEEE Communications Magazine, 57(1), 20-25. https://doi.org/10.1109/MCOM.2018.1800414
Zamani, M., & Giaglis, G. M. (2021). Decision support systems in healthcare: A review. Information Systems Frontiers, 23(3), 1-18. https://doi.org/10.1007/s10796-021-10105-3
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.



