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Laila Hendrina
Universitas Prima Indonesia
Computer Science & IT Economics, Econometrics & Finance Languange, Linguistic, Communication & Media

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Analysis of Sales Vitamins Drugs Covid-19 Pandemic with the Random Forest Method Yennimar Yennimar; Miko Pasaribu; Laila Hendrina; Ayu Widila; Dono Sitinjak
Jurnal Mantik Vol. 5 No. 3 (2021): November: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

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Abstract

During the covid-19 pandemic that occurred in Indonesia until the new normal period, consumer demand for a vitamin drug was fast and unpredictable, thus making pharmacies must be able to plan the optimal supply of vitamin drugs based on the graph of public demand during the pandemic and new normal. This means that the pharmacy does not experience a shortage of stock or excess stock. Therefore, all systems that can predict sales of vitamin drugs are needed during the new normal pandemic. To be able to make predictions, an appropriate method is needed to get accurate results. One of them is the Random Forest method. With Random Forest, the data is predicted based on attribute data so as to produce a conclusion about the value of the desired attribute. Based on this study, 200 sales data of vitamin drugs were taken during the pandemic and new normal with categories of vitamin B complex drugs, vitamins C, D, E, K and Multivitamins and the attributes used were vitamin brand, category, sales conditions, price and sales category. and doesn't work. The test results from this study, it was found that the prediction of vitamin drug sales during the new normal pandemic using the Random Forest method obtained 100% accuracy for testing data with a composition of 80:20, 70:30 and 60:40, so that vitamin drugs would still be sold in new normal.
Co-Authors Ayu Widila Dono Sitinjak Miko Pasaribu Yennimar Yennimar