BOTika: A Pharmaceutical Management System Using Seasonal Autoregressive Integrated Moving Average (SARIMA) and Clustering Algorithm

This study introduces “BOTika: A Pharmaceutical Management System,” which incorporates the Seasonal Autoregressive Integrated Moving Average (SARIMA) model and a Clustering Algorithm to tackle significant challenges faced by small and medium-sized pharmacies in Metro Manila. BOTika is designed to streamline and enhance pharmaceutical operations, focusing on areas such as inventory control, sales monitoring, profit evaluation, and medication management. Its primary goal is to improve efficiency in pharmacy operations, particularly through predictive analytics powered by the SARIMA model. The system also uses a Retrieval Report Algorithm for data retrieval and Statistical Analytics for data interpretation. Additionally, a Clustering Algorithm is employed to group medicines by key characteristics, enabling targeted discounts and promotions. The system's interface, developed as a Progressive Web App (PWA), allows administrators to manage operations seamlessly, while customers benefit from a pre-order feature. Results demonstrate that the SARIMA model provides accurate demand forecasts, leading to better decision-making in pharmacy management. Ultimately, the project aims to modernize pharmacy operations, enhance customer experience, and support the sector's growth, contributing to both sustainable practices and economic progress in the region.

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Published
2024-12-12
DOI
https://doi.org/10.1109/icses63760.2024.10910563
Primary Topic
Advanced Statistical Process Monitoring
Type
article
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article

BOTika: A Pharmaceutical Management System Using Seasonal Autoregressive Integrated Moving Average (SARIMA) and Clustering Algorithm

Criselle J. Centeno, Ariel Antwaun Rolando C. Sison, Jamillah Guialil, Nicole D. Bacani et al.
Advanced Statistical Process Monitoring
article

BOTika: A Pharmaceutical Management System Using Seasonal Autoregressive Integrated Moving Average (SARIMA) and Clustering Algorithm

Criselle J. Centeno, Ariel Antwaun Rolando C. Sison, Jamillah Guialil, Nicole D. Bacani, Dwayne Douglas C. Balitustus, Christel S. Porcalla
article en

Abstract

This study introduces “BOTika: A Pharmaceutical Management System,” which incorporates the Seasonal Autoregressive Integrated Moving Average (SARIMA) model and a Clustering Algorithm to tackle significant challenges faced by small and medium-sized pharmacies in Metro Manila. BOTika is designed to streamline and enhance pharmaceutical operations, focusing on areas such as inventory control, sales monitoring, profit evaluation, and medication management. Its primary goal is to improve efficiency in pharmacy operations, particularly through predictive analytics powered by the SARIMA model. The system also uses a Retrieval Report Algorithm for data retrieval and Statistical Analytics for data interpretation. Additionally, a Clustering Algorithm is employed to group medicines by key characteristics, enabling targeted discounts and promotions. The system's interface, developed as a Progressive Web App (PWA), allows administrators to manage operations seamlessly, while customers benefit from a pre-order feature. Results demonstrate that the SARIMA model provides accurate demand forecasts, leading to better decision-making in pharmacy management. Ultimately, the project aims to modernize pharmacy operations, enhance customer experience, and support the sector's growth, contributing to both sustainable practices and economic progress in the region.

University of the City of Manila (PH)
Zero hunger
Openalex Percentile: Top 73%
Advanced Statistical Process Monitoring
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