<![CDATA[The rapid advancement of information technology has encouraged various business sectors to enhance efficiency in data management, particularly in the financial domain. Has Jaya Automotive Workshop still relies on manual record-keeping for transaction management and financial reporting, which poses risks such as recording errors, delays in report generation, and difficulties in decision-making. This study aims to develop a web-based financial information system to improve transaction management efficiency and provide accurate, structured, and informative financial data. The research employs a software engineering approach using the Waterfall development model, encompassing requirements analysis, system design, implementation, and testing. The system is developed using containerization technology with Docker to ensure ease of deployment and environmental consistency. Additionally, Machine Learning is integrated using a linear regression algorithm to predict profit and loss based on historical data. The results indicate that the developed system simplifies transaction recording, accelerates financial reporting, and presents data visualization in graphical form to enhance user understanding of financial conditions. The prediction feature provides an estimate of future financial performance, although the model’s accuracy remains relatively limited due to fluctuating data characteristics. Overall, the system improves the efficiency and effectiveness of financial management and adds value in supporting data-driven decision-making at Has Jaya Automotive Workshop.]]>
