Implementasi Algoritme Average-Based Length Dalam Fuzzy Time Series untuk Memprediksi Pasien Rumah Sakit - Martono; Barkah Hendrardi (Lembaga Penelitian dan Pengabdian kepada Masyarakat (LPPM) Politeknik Pratama Mulia Surakarta, 2019)
Hospitals as providers of services in the health sector, are required to provide the best service to the community. Improved services are shown by improving hospital management, such as the management of existing resources optimally. In management, planning is the initial activity stage and is very important because it can define the goals, strategies, and directions needed. The number of patient visits is fluctuating and the exact number cannot be predicted, causing the planning that has been made to be inefficient. In an effort to anticipate these problems and support planning management, it is necessary to estimate or predict. In this study using the Fuzzy Time Series method with Average-Based Length Algorithm which is packaged in a computing application to predict the number of patient visits Central Surgery Installation at Permata Medika Hospital Semarang. The algorithm is able to determine the effective interval length, so that it can provide predictive results with a good degree of accuracy, thus the prediction results can be used in supporting decision making for the leaders of Permata Medika Hospital Semarang quickly, effectively, and accurately.