Abstract
Online shopping has become one of the most prominent forms of retail for businesses. This is due to the advancement of web services, and mobile applications that have become accessible, and effective with the utilization of the Internet. Accordingly, this study aims to further scrutinize the discussed application of online shopping. Therefore, an online retail system with mobile application through Android was developed, deployed with the purpose of managing the products, and services that are offered by the company, with the standardization of data forecasting to make accurate prediction of future trends. To standardize and validate the attributes of the said system, a descriptive research method that used a survey instrument based on the Likert scale, and the functionality, usability, reliability, performance, and supportability (FURPS) model. The said survey instrument collected 200 responses with purposeful sampling treatment and converted into distinct inputs with the use of the weighted mean formula. The functionality, usability, and reliability were rated as acceptable, with weighted means of 4.5, 4.5, and 4.5, respectively. The performance and supportability were rated as perfectly acceptable, with weighted mean scores of 4.7 and 4.6, accordingly. The system’s overall attributes were rated perfectly acceptable, with a weighted mean of 4.6, suggesting that it managed and analyzed sales, services, and inventory data.
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Juanatas, I.C. et al. (2023). Online Retail System with Data Forecasting and Android Mobile Application. In: Nagar, A.K., Singh Jat, D., Mishra, D.K., Joshi, A. (eds) Intelligent Sustainable Systems. Lecture Notes in Networks and Systems, vol 578. Springer, Singapore. https://doi.org/10.1007/978-981-19-7660-5_18
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DOI: https://doi.org/10.1007/978-981-19-7660-5_18
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