OPTIMIZING THE PROCUREMENT OF MEDICAL STAFF AT THE RAHMANI CLINIC USING THE SARIMA AND ABK KES METHODS

Abstract

Optimal planning of medical staff is very important for the sustainability of a clinic. This study aims to determine the optimal number of doctors at Rahmani Clinic based on predictions of the number of patients each month in 2025. The method used is Seasonal Autoregressive Integrated Moving Average (SARIMA) to predict the number of patients, and Health Workload Analysis (ABK-Kes) to determine the number of doctors needed. From the prediction results, the average number of patients visiting each month is in the range of 2,000 to 3,000 general practitioner patients and 100 to 200 dentist patients. Based on the results of the ABK-Kes analysis, the optimal number of doctors needed is 5 general practitioners and 1 dentist per month. Furthermore, the optimization of doctors' working hours identified 8 hours of overtime for the main doctor, indicating the need to improve the doctor's schedule at Rahmani Clinic.
Keywords: Patient Prediction, SARIMA, ABK-Kes, Medical Staff Optimization