Prediction of Whole Blood Stock Using Single Exponential Smoothing: A Case Study at the Indonesian Red Cross, Semarang - Adha Wiyan Hayyannabil; Aris Tri Joko Harjanto; Bambang Agus Herlambang (Program Studi Sistem Informasi, Fakultas Sains dan Teknologi, Universitas Islam Negeri Raden Fatah Palembang, 2024)
The Indonesian Red Cross, as a provider of public health services in the city of Semarang, experienced a shortage of whole blood supply in April 2023 due to high demand. In response to this issue, an effective prediction system is needed. This research aims to apply the single exponential smoothing method to predict blood needs at the Indonesian Red Cross in Semarang. The study uses data from 2022 to April 2024 as historical data to forecast blood requirements. The research findings indicate a continuous increase in the demand for whole blood availability. This study provides a foundation for developing a better prediction system with more complex data patterns.