Application For Petty Cash Management

Muhammad Hazim Muhamad Norung (1), Shahreen Kasim (2), - Defni (3)
(1) Faculty of Computer Science and Technology, Universiti Tun Hussein Onn, Parit Raja, 86400, Malaysia
(2) Faculty of Computer Science and Technology, Universiti Tun Hussein Onn, Parit Raja, 86400, Malaysia
(3) Department of Information Technology, Politeknik Negeri Padang, Indonesia
Fulltext View | Download
How to cite (IJASEIT) :
Norung, M. H. M., Kasim, S., & Defni, .-. (2020). Application For Petty Cash Management. International Journal of Advanced Science Computing and Engineering, 2(3), 97–107. https://doi.org/10.62527/ijasce.2.3.102
Some people currently face into traps of dept and overspending without even realizing it. The feeling of never having enough cash or living paycheck to paycheck can lead serious final problems that can lead into financial difficulties over a lifetime. This study aims to determine how application can manage the financial problems. Specifically, it manages on how you spend your money and get the overview about it. In this application, it uses financial skills such as budgeting, saving and spending. It refers to the strategies technique to determine the use of an individual. To achieve a better understanding on the money management, a report is created to see the whole month transaction such as saving and spending. The report will show the total amount of money spent and where the money is going. You will understand your expenses with the report and create a budget for future expenses. By having good financial skills, you can have a strategy on how you want to manage your money. Creating and sticking to a budget might seem tough to achieve but it helps us to see full transparency our financial situation.

Mithe, R., Indalkar, S., & Divekar, N., "Optical character recognition," International journal of recent technology and engineering (IJRTE), vol. 2(1), pp. 72-75, 2013.

J. M. White and G. D. Rohrer, "Image Thresholding for Optical Character Recognition and Other Applications Requiring Character Image Extraction," in IBM Journal of Research and Development, vol. 27, no. 4, pp. 400-411, July 1983, doi: 10.1147/rd.274.0400.

Kai Ding, Zhibin Liu, LianwenJin, Xinghua Zhu, A Comparative study of GABOR feature and gradient feature for handwritten 17hinese character recognition, International Conference on Wavelet Analysis and Pattern Recognition, pp. 1182-1186, Beijing, China, 2-4 Nov. 2007.

Rao, N. Venkata, et al. "Optical Character Recognition Technique Algorithms." Journal of Theoretical & Applied Information Technology, 2016.