Pemodelan Sistem Interaksi Obat dengan Menggunakan Fuzzy Inference System dan Pareto Optimality

• Main Authors: Elena Yustina, Subanar Subanar
• Format: Article
• Language: English
• Published: Universitas Gadjah Mada 2013-01-01
• Series: IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
• Online Access: https://jurnal.ugm.ac.id/ijccs/article/view/2038

Drug interactions is the interaction occurs between drugs that consumption simultaneously. Drug interactions can produce a good effect on patients, but not rarely produce adverse effects. Patients with diabetes and hypertension expected to control blood pressure and blood glucose levels to remain in normal circumstances, it is necessary to consider the use of medications for both diseases in order to produce effective therapies. Pareto optimality is a popular concept in the determination optimal solution of multiobjective problems. In determining the optimal solution of multiobjective problem should pay attention for each objective function, frequently conflicting objective functions. The interaction of two drugs has two objective function that is maximizing the positive effects and minimize negative effects. So its use is necessary to find optimal solutions to achieve the expected therapeutic. This research using Fuzzy Inference Sistem (FIS) to determine the appropriate medication to keep blood pressure and blood glucose levels of patients with hypertension and diabetes under control in normal and Pareto optimality to determine drug optimal solution. Fuzzy Inference System generates output choice of drug classes based on fuzzy rules in accordance with the patient's disease condition. Pareto optimality produces a pair solution for diabetes and hypertension drug that satisfy thresholds the minimum effective level (Minimum Effective Concentration; MEC) and maximum toxic levels (Minimum Toxic Concentration; MTC) of each drug.