Abstract:
designed for managing personal finances. The application allows users to register and log
in using email and password authentication. Once logged in, users have a dashboard
displaying essential financial information such as monthly income, spending, balance, and
net worth. The application's main feature is the "Pocket" page, where users can create
different pockets, including options like Cash, Bank account, and e-wallet. Users can
specify the pocket type, name, current balance, and description. Actions such as
transferring funds between pockets, editing details, deleting pockets, and reviewing pocket
transactions are available. The "Transaction" page enables users to add three types of
transactions: income, spending, and transfers. Within the stocks section, a machine learning
algorithm is incorporated to predict future stock prices.
To predict stock prices, the algorithm collects historical data from the Yahoo Finance API,
converts it to a structured panda's data frame-like format, and extracts the necessary
features and target variables. By making predictions on new data, the algorithm provides
users with insights into potential stock price fluctuations, indicating potential upsides or
downsides. Least Squares Regression is a popular algorithm used for predicting numerical
values based on input features. It aims to find the best-fitting line that minimizes the sum
of the squared differences between the predicted values and the actual values in a given
dataset.
The web application is developed using the Laravel PHP framework, with a MySQL
database and Apache server utilized for storage and hosting purposes. By combining
personal finance management features with stock price prediction, the application offers
users a powerful tool for making informed financial decisions
