Analisis Data Stok Alat Kesehatan menggunakan Metode Regresi Linier Berdasarkan Nilai RMSE - Trian Nurmansyah; Rudi Kurniawan; Yudhistira Arie Wijaya (Jurnal Informatika dan Rekayasa Perangkat Lunak, 2024)
Inventory of healthcare equipment, whether in hospital or clinic settings, represents a significant investment requiring substantial cost allocation. However, estimating these equipment needs often relies solely on the overall available stock, as monthly or yearly requirements tend to fluctuate. Consequently, this approach leads to an inability to meet all necessary equipment needs, resulting frequently in surplus inventory. Therefore, anticipating this issue requires predicting healthcare equipment stock at Klinik Pembina Sehat. This study aims to forecast equipment stock using the linear regression algorithm method. The selection of this algorithm is due to its suitability in handling the linear relationship between dependent and independent variables. Research findings demonstrate the developed model's ability to predict healthcare equipment stock with a reasonably high level of accuracy, with a Root Mean Square Error (RMSE) value of 93.359. This value signifies a relatively low prediction error, indicating the model's precision in estimating stock requirements. Thus, this research holds the potential to enhance operational efficiency in managing healthcare equipment stock within the clinic and serves as a foundation for further studies to improve stock planning processes in similar healthcare institutions.