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Development and implementation of the Fintrack application as a financial planner for students at Unika Soegijapranata Semarang Nugraha, Johanes Arya Pramesta; Sanjaya, Ridwan; Koeswoyo, Freddy
SISFORMA Vol 12, No 1: May 2025
Publisher : Soegijapranata Catholic University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24167/sisforma.v12i1.13150

Abstract

The increasing demand for financial literacy among students highlights the importance of effective financial management tools. Many students face challenges in managing their finances, such as budgeting, tracking expenses, and planning savings. Addressing these issues, the Fintrack application was developed as a financial planning tool tailored for students at Unika Soegijapranata Semarang.  The application utilizes modern technologies like Flutter for cross-platform development and Firebase for real-time data management. Its features include daily transaction recording, budget analysis with pie charts, and automated financial ratio calculations. The application also provides downloadable monthly financial reports, including detailed transaction logs and financial analyses, aiming to enhance user decision-making.  The primary goal of Fintrack is to empower students with tools to better manage their finances, improve their financial literacy, and make informed financial decisions. By integrating intuitive interfaces, automated financial insights, and practical features, the application serves as a reliable companion for students in overcoming financial challenges and achieving long-term financial stability.
Image Processing on Plastic Bottle Reverse Vending Machine to Enhance Community Plastic Waste Management Nugraha, Johanes Arya Pramesta; Sanjaya, Ridwan; Koeswoyo, Freddy; Pamudji, Andre Kurniawan
SISFORMA Vol 12, No 1: May 2025
Publisher : Soegijapranata Catholic University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24167/sisforma.v12i1.13531

Abstract

The problem of plastic waste is being addressed in a variety of ways, ranging from manual waste sorting to reverse vending machines. On the other side, businesses are becoming increasingly concerned about waste management. Several ways to producing reverse vending machines have been tested, including the use of plastic sensors. However, the findings were unsatisfactory due to imprecise detection. This study looks into the use of ESP32-Cam combined with machine learning for high-precision plastic bottle detection in reverse vending machines. It is envisioned that high-precision plastic bottle detection would be used in reverse vending machines. It is intended that by providing an incentive for each identified plastic bottle, people will be motivated to collect plastic bottles and deposit them into reverse vending machines, thereby supporting digital humanities through enhanced waste management practices.