For managers and business owners in the hospitality and retail industry, one of the most repetitive tasks is rota scheduling. Managers also struggle weekly to find a healthy balance between scheduling enough staff to meet the demands of the business while keeping the morale of the employees high. Some managers are not aware that the latter is just as if not more important than the first. This report investigates the powers of machine learning and predictive analysis and how it can make an immense change to the way businesses operate. I have created a web-based software application that will make use of the Naïve Bayes algorithm to predict the shift start and end time for employees accurately. The model will also consider a range of factors that determine the shift start time and end time staff members will do. It will also be the central hub for all rota related matters, allowing all staff members to manage their holidays and view the shifts they are working. While there were some challenges during the project duration, the resulting application is both simple and powerful. Managers and business owners will be able to benefit significantly from the features the application offers, and so will their business.
AutoRota requires Java 8 to run. The application is currently running on a MySQL localhost sever. Details can be found in the src/main/resources/ application.properties
To run the project on terminal run the following command:
gradlew bootrun
./gradlew bootrun
If there are any issues with the API calls, please check respective websites for details an check status Weather: WeatherBit Bank Holiday: Calendarific