Bibliographic citations
Torres, E., (2024). Sistema web basado en un modelo de recomendación de Machine Learning para apoyar el proceso de ventas en una ferretería [Universidad Católica Santo Toribio de Mogrovejo]. http://hdl.handle.net/20.500.12423/8054
Torres, E., Sistema web basado en un modelo de recomendación de Machine Learning para apoyar el proceso de ventas en una ferretería []. PE: Universidad Católica Santo Toribio de Mogrovejo; 2024. http://hdl.handle.net/20.500.12423/8054
@misc{renati/1107203,
title = "Sistema web basado en un modelo de recomendación de Machine Learning para apoyar el proceso de ventas en una ferretería",
author = "Torres Segovia, Eduar Enrique",
publisher = "Universidad Católica Santo Toribio de Mogrovejo",
year = "2024"
}
The research project aimed to develop a web sales system based on a Machine Learning recommendation model to support the sales process in the hardware store López y Cía. S.A.C. To this end, the following specific objectives were proposed: to determine the most appropriate Machine Learning technique to implement the recommendation model in the hardware store, to generate the recommendation model using the data from the hardware store and the selected technique, to build a sales web application that integrate the generated recommendation model and validate the web application based on the ISO 25010 standard. To achieve this, the CRISP-DM methodology was used and Python, HTML, Google Colab, and MySQL were used as a database manager. It was determined that the most appropriate Machine Learning technique to implement the recommendation model was FP Growth. In addition, a recommendation model was generated using the aforementioned technique and 208,535 records of sales made between the years 2021 and 2022, achieving a model accuracy of 90%. After this, a web application was built where the generated recommendation model was integrated. Finally, the web application was validated, where it was shown that it met the quality criteria established by the ISO 25010 standard.
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