最小二乘法预测药品库存

N. Dengen, Haviluddin, Lia Andriyani, M. Wati, E. Budiman, F. Alameka
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引用次数: 8

摘要

卫生组织非常有必要规划活动,以确保按类别和数量提供药物。因此,本研究将最小二乘(LS)方法作为规划的一部分,基于过去的药品消费数据进行预测,以保证药品的可得性。本研究使用了2017年1 - 11月的药品消费数据,共197个样本数据集。根据实验结果,对下一个月的预测具有平均精度值,平均绝对偏差(MAD)为51.20%,均方误差(MSE)为66.29%,平均绝对百分比误差(MAPE)为10%。也就是说,LS方法可以作为药物可获得性的替代预测方法进行探索。此外,利用计算智能(CI)方法提高精度是下一步的研究计划。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Medicine Stock Forecasting Using Least Square Method
A planning activities in order to ensure drug availability according category and quantity is very necessary by health organizations. Therefore, this study, Least Square (LS) method for forecasting as a part of planning in order to guarantee the drugs availability based on drugs consumption past data have been implemented. In this study, drugs consumption data in period January - November 2017 or 197 samples datasets have been utilized. Based on the experimental results, the prediction for the next month has an average accuracy value, Mean Absolute Deviation (MAD) of 51.20 %, Mean Square Error (MSE) of 66.29 % and Mean Absolute Percentage Error (MAPE) of 10% has been obtained. In other words, the LS method could be explored as an alternative forecasting method of drugs availability. Furthermore, an accuracy increased improved by using the computational intelligence (CI) method is next research plan.
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