Expense Tracker Application using Naive Bayes

Expense Tracker Application using Naive Bayes

  IJRES-book-cover  International Journal of Recent Engineering Science (IJRES)          
  
© 2023 by IJRES Journal
Volume-10 Issue-3
Year of Publication : 2023
Authors : Raj Thakare, Ninad Thakare, Raj Sangtani, Shubham Bondre, Amitkumar Manekar
DOI : 10.14445/23497157/IJRES-V10I3P108

How to Cite?

Raj Thakare, Ninad Thakare, Raj Sangtani, Shubham Bondre, Amitkumar Manekar, "Expense Tracker Application using Naive Bayes ," International Journal of Recent Engineering Science, vol. 10, no. 3, pp. 50-56, 2023. Crossref, https://doi.org/10.14445/23497157/IJRES-V10I3P108

Abstract
This study introduces an Expense Tracker mobile application that utilizes the Naive Bayes algorithm for automated expense tracking. The app, developed for Android users using Kotlin and XML in Android Studio, allows manual entry of expenses and automatic detection of bank messages. The Naive Bayes algorithm is employed to classify these messages. The app provides visual representations of expenses through Pie Charts for multiple time frames such as monthly, weekly, yearly etc. It helps users gain insights into their spending habits. With Firebase as the online database, data persistence is ensured even if the app is uninstalled. Overall, the Expense Tracker app offers a user-friendly solution for individuals to manage their finances effectively and make informed decisions about their expenses.

Keywords
Machine learning, Personal finance management, Expense tracking, Predictive modeling, User interface.

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