E3S Web Conf.
Volume 73, 2018The 3rd International Conference on Energy, Environmental and Information System (ICENIS 2018)
|Number of page(s)||6|
|Section||System Information and Decision Support System|
|Published online||21 December 2018|
Forecasting and Controlling the Food Supply System in Hospital Using Exponential Smoothing
1 Magister of Information System, School of Postgraduate Studies, Diponegoro University, Semarang - Indonesia 50242
2 Department of Statistics, Faculty of Science and Mathematics, Diponegoro University, Semarang - Indonesia 50275
3 Department of Informatics, Faculty of Engineering, Diponegoro University, Semarang - Indonesia 50275
* Corresponding author: firstname.lastname@example.org
The satisfaction of patient care is an indicator of good performance in hospitals, one of which plays a critical role is a logistic serving of food. With the fluctuating number of patients, the hospital should be able to meet the demand for the number of patients each day. This study aims to build the system of forecasting and controlling the food supplies to determine the number of servings of food supplies in the next period. The implementation of Exponential Smoothing method is used to predict the number of servings should be available for the next period. Amount of food raw material is controlled using re-orders point model, it aims to anticipate the occurrence of stockout with the minimum amount of food provides should be available. The data were obtained from the requested amount of food during 212 days for three times, morning, noon, and night. Forecasting values using alpha parameters 0.3 and 0.7 with a minimum forecasting error calculation using MAPE for alpha 0.7 with a value 12.81% for morning time, 11.59% during the day, and 10.96% night time. Forecasting result not only can be used to allocate food supplies but also to control stock of raw material food.
Key words: Forecasting Method / Exponential Smoothing / Re-Order Point
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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