Forecasting of pharmaceutical products using arima model and exponential smoothing / Nur Hayatul Afza Mohamed Fishal

The pharmaceutical industry creates, manufactures, and sells vaccines or pharmaceutical drugs as medications to be prescribed (or self-administered) by patients for healing, vaccinating, or alleviating symptoms. The expiry date is the most important thing to be aware of to avoid consumer purchasing...

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Main Author:	Mohamed Fishal, Nur Hayatul Afza
Format:	Thesis
Language:	English
Published:	2021
Subjects:	Time-series analysis
Online Access:	https://ir.uitm.edu.my/id/eprint/44469/1/44469.pdf
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id	my-uitm-ir.44469
record_format	uketd_dc
spelling	my-uitm-ir.444692021-04-22T06:13:28Z Forecasting of pharmaceutical products using arima model and exponential smoothing / Nur Hayatul Afza Mohamed Fishal 2021-03-30 Mohamed Fishal, Nur Hayatul Afza Time-series analysis The pharmaceutical industry creates, manufactures, and sells vaccines or pharmaceutical drugs as medications to be prescribed (or self-administered) by patients for healing, vaccinating, or alleviating symptoms. The expiry date is the most important thing to be aware of to avoid consumer purchasing an expired product. It would harm their well-being where the customer then may take legal actions. Therefore, it is crucial to know how much to stock up the product. In this research, the selected methods include a single and double exponential smoothing model and the ARIMA model. Data on two types of pharmaceutical products, Paracap 500mg and Bena Expectorant 120ml, were collected from a pharmacy’s database in Kangar from January 2015 to December 2019. Microsoft Excel and R Programming were used to analyze the data. As the result, between both exponential smoothing models, single exponential smoothing is the best model to forecast the demand of Paracap 500mg and Bena Expectorant 120ml. For the ARIMA model, depending on the smallest value of MSE, ARIMA (2,1,1) is the best model to forecast the demand of Paracap 500mg, while ARIMA (1,1,2) for Bena Expectorant120ml. Finally, for the final and the best option, a comparison of MSE, RMSE and MAPE values was made between single exponential smoothing and ARIMA model for Paracap 500mg and Bena Expectorant 120ml. The result indicates that single exponential smoothing has been selected for both product as the best model to forecast the demand starting from January 2020. 2021-03 Thesis https://ir.uitm.edu.my/id/eprint/44469/ https://ir.uitm.edu.my/id/eprint/44469/1/44469.pdf text en public degree Universiti Teknologi MARA Perlis Faculty of Computer & Mathematical Sciences
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
topic	Time-series analysis
spellingShingle	Time-series analysis Mohamed Fishal, Nur Hayatul Afza Forecasting of pharmaceutical products using arima model and exponential smoothing / Nur Hayatul Afza Mohamed Fishal
description	The pharmaceutical industry creates, manufactures, and sells vaccines or pharmaceutical drugs as medications to be prescribed (or self-administered) by patients for healing, vaccinating, or alleviating symptoms. The expiry date is the most important thing to be aware of to avoid consumer purchasing an expired product. It would harm their well-being where the customer then may take legal actions. Therefore, it is crucial to know how much to stock up the product. In this research, the selected methods include a single and double exponential smoothing model and the ARIMA model. Data on two types of pharmaceutical products, Paracap 500mg and Bena Expectorant 120ml, were collected from a pharmacy’s database in Kangar from January 2015 to December 2019. Microsoft Excel and R Programming were used to analyze the data. As the result, between both exponential smoothing models, single exponential smoothing is the best model to forecast the demand of Paracap 500mg and Bena Expectorant 120ml. For the ARIMA model, depending on the smallest value of MSE, ARIMA (2,1,1) is the best model to forecast the demand of Paracap 500mg, while ARIMA (1,1,2) for Bena Expectorant120ml. Finally, for the final and the best option, a comparison of MSE, RMSE and MAPE values was made between single exponential smoothing and ARIMA model for Paracap 500mg and Bena Expectorant 120ml. The result indicates that single exponential smoothing has been selected for both product as the best model to forecast the demand starting from January 2020.
format	Thesis
qualification_level	Bachelor degree
author	Mohamed Fishal, Nur Hayatul Afza
author_facet	Mohamed Fishal, Nur Hayatul Afza
author_sort	Mohamed Fishal, Nur Hayatul Afza
title	Forecasting of pharmaceutical products using arima model and exponential smoothing / Nur Hayatul Afza Mohamed Fishal
title_short	Forecasting of pharmaceutical products using arima model and exponential smoothing / Nur Hayatul Afza Mohamed Fishal
title_full	Forecasting of pharmaceutical products using arima model and exponential smoothing / Nur Hayatul Afza Mohamed Fishal
title_fullStr	Forecasting of pharmaceutical products using arima model and exponential smoothing / Nur Hayatul Afza Mohamed Fishal
title_full_unstemmed	Forecasting of pharmaceutical products using arima model and exponential smoothing / Nur Hayatul Afza Mohamed Fishal
title_sort	forecasting of pharmaceutical products using arima model and exponential smoothing / nur hayatul afza mohamed fishal
granting_institution	Universiti Teknologi MARA Perlis
granting_department	Faculty of Computer & Mathematical Sciences
publishDate	2021
url	https://ir.uitm.edu.my/id/eprint/44469/1/44469.pdf
_version_	1783734718885265408

Forecasting of pharmaceutical products using arima model and exponential smoothing / Nur Hayatul Afza Mohamed Fishal

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