Analisys Of Demand and Optimization Of Medicine Prediction Using ABC Analysis and SVR Method In The “MORBIS” Aplication

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Tutik Maryana Kusrini Kusrini Hanif Al Fatta


The problem that occurs in hospitals regarding the processing of drug supplies is about the condition of out of stock medicines because hospitals spend around 33% of the total investment in one year only for the investment costs of drugs. To deal with the above problems the hospital must have good logistics management, one way of managing it is by doing good planning. In this research, the writer will use ABC Analysis and Support Vector Regression (SVR) algorithm. For the use of these methods, the following ABC Analysis will be used for the drug classification process, namely by dividing the torch into three main groups based on interests, namely groups A, B and C. Henceforth, the writer will use the SVR motedo to calculate drug predictions. The results that the authors get from this study are ABC analyys classify drugs. Into three groups namely group A with a total of 276 items with a percentage of 22.96% of the total number of items, group B with a total of 396 items with a percentage of 33.11% and C with a total of 528 with a percentage of 43.94% with a total of 1202 drug items. Prediction testing is done by taking a sample of five drugs derived from group classification. The SVR calculation process is done by comparing linear scaling and z normalization preprocessing methods. The result of this research is that MAPE shows that preprocessing with linear scaling produces a better value than compared to z nomrlization and calculation with ABC analysis.


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T. Maryana, K. Kusrini, and H. Fatta, “Analisys Of Demand and Optimization Of Medicine Prediction Using ABC Analysis and SVR Method In The ‘MORBIS’ Aplication”, CCIT Journal, vol. 13, no. 2, pp. 147-154, Aug. 2020.