PREDIKSI JUMLAH PASIEN RAWAT INAP MENGGUNAKAN METODE DOUBLE EXPONENTIAL SMOOTHING DI RSU CUT MEUTIA KOTA LHOKSEUMAWE: Prediksi Jumlah Pasien - Eriska Hamida Sihotang; Dahlan Abdullah; Nunsina (Rabit : Jurnal Teknologi dan Sistem Informasi Univrab, 2025)
The increasing number of inpatient visits at hospitals requires better and more accurate planning by healthcare facilities. Poor planning can lead to an imbalance between the number of patients and the available resources, such as hospital beds, medical personnel, and medications. This study aims to develop a forecasting system for predicting the number of inpatients using the  (DES) method at RSU Cut Meutia Kota Lhokseumawe. The DES method is chosen because it is capable of handling historical data that exhibits trend patterns without seasonal components. The data used in this study consists of daily inpatient records from 2022 to 2024. The forecasting process involves testing several alpha and beta values to determine the most optimal parameter combination, which yields the highest accuracy based on the Mean Absolute Percentage Error (MAPE). The forecasting system is developed using Python programming language and produces outputs in the form of graphs and daily prediction tables. The results show that the DES method provides accurate forecasts and can assist in improving inpatient capacity planning and overall hospital resource management.