Proceedings of the 2nd International Conference on Neural Networks and Machine Learning 2023 (ICNNML 2023)

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Drug Sales Forecasting Using Single Exponential Smoothing (Case Study: NDM Pharmacy)

Authors
Muhammad ‘Ariful Furqon1, Erik Razasyah Fahlefi1, Nelly Oktavia Adiwijaya1, *
1Jl. Kalimantan Tegalboto No.37, 68121, Jember, Indonesia
*Corresponding author. Email: nelly.oa@unej.ac.id
Corresponding Author
Nelly Oktavia Adiwijaya
Available Online 29 June 2024.
DOI
10.2991/978-94-6463-445-7_4How to use a DOI?
Keywords
Inventory forecasting; single exponential smoothing; pharmaceutical sales analysis
Abstract

NDM Pharmacy is a pharmaceutical retail establishment. A production production plan is vital to operational management, especially concerning inventory availability. Presently, NDM Pharmacy needs help accurately forecasting future inventory levels, particularly for three distinct categories of pharmaceuticals. This study utilizes the Single Exponential Smoothing approach to predict pharmaceutical sales in the drugstore. The analysis utilizes drug sales data from January 2022 to December 2022, which reveals a consistent average with oscillations in a horizontal pattern. The research findings demonstrate that the single exponential smoothing method uses several alpha values for optimal weight values. The assessment of forecasting accuracy is determined by the value of the Mean Absolute Percentage Error (MAPE), with a smaller MAPE indicating a higher level of accuracy in forecasting. The forecasting findings indicate that the single exponential smoothing yields the lowest MAPE for three medications, with alpha values of 0.1, 0.4, and 0.3, respectively. The MAPE for the three categories of medications is 11.96843%, 14.55955%, and 13.9353%, respectively. This study offers valuable insights for NDM Pharmacy in strategizing the future supply of pharmaceutical stock and improving the accuracy of sales predictions.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2nd International Conference on Neural Networks and Machine Learning 2023 (ICNNML 2023)
Series
Advances in Intelligent Systems Research
Publication Date
29 June 2024
ISBN
10.2991/978-94-6463-445-7_4
ISSN
1951-6851
DOI
10.2991/978-94-6463-445-7_4How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Muhammad ‘Ariful Furqon
AU  - Erik Razasyah Fahlefi
AU  - Nelly Oktavia Adiwijaya
PY  - 2024
DA  - 2024/06/29
TI  - Drug Sales Forecasting Using Single Exponential Smoothing (Case Study: NDM Pharmacy)
BT  - Proceedings of the 2nd International Conference on Neural Networks and Machine Learning 2023 (ICNNML 2023)
PB  - Atlantis Press
SP  - 25
EP  - 31
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-445-7_4
DO  - 10.2991/978-94-6463-445-7_4
ID  - Furqon2024
ER  -