Rajvardhan Thakare, Ninad Thakare, Raj Sangtani, Shubham Bondre, A. Manekar
{"title":"Expense Tracker Application using Naive Bayes","authors":"Rajvardhan Thakare, Ninad Thakare, Raj Sangtani, Shubham Bondre, A. Manekar","doi":"10.14445/23497157/ijres-v10i3p108","DOIUrl":null,"url":null,"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.","PeriodicalId":14292,"journal":{"name":"International Journal of Recent Engineering Science","volume":"296 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Recent Engineering Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14445/23497157/ijres-v10i3p108","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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.