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Agile Scrum Integration In Designing Statistics Modules Hpp Reports In Applications (Ta Cashier) Ansar, Ansar; B, Isdayani.; Siswanto, Rahmat
Brilliance: Research of Artificial Intelligence Vol. 5 No. 1 (2025): Brilliance: Research of Artificial Intelligence, Article Research May 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i1.6378

Abstract

The advancement of information technology, especially in the development of web-based applications, has made a major contribution in improving the efficiency of business operations, including in point-of-sales (POS) systems. Based on observations and interviews conducted at the student cooperative of Muhammadiyah University of Palopo, it was found that the cashier system used did not yet have goods statistics features and cost of goods sold (COGS) reports. Therefore, this study aims to design and develop these two important modules using the Agile Scrum approach. The method used is Agile Development with the Scrum framework, which is divided into several sprints with measurable development targets. The system is developed using the Laravel framework and MySQL database. The two main modules built are (1) Goods statistics which displays the number of products sold per day, week, and month, and (2) COGS report which calculates the total cost of goods sold and profit margin based on purchase and sales data. The development results show that both modules function according to user needs. The Statistics module can display real-time data that is relevant for sales evaluation, while the COGS module is able to calculate the cost of goods sold accurately and present complete financial reports. Validation is carried out through sprint reviews and user acceptance tests (UAT), which show that these features facilitate the business decision-making process. In conclusion, the integration of the Agile Scrum method in POS application development has proven effective in building analytical features that are relevant and adaptive to the needs of MSMEs.