Developing emergency application for LRT passengers with decision tree algorithm (RailAlert!) / Ezrren Natasha Baddru’l-Sham … [et al.] - Baddru’l-Sham, Ezrren Natasha; Abdul Rahid @ Abdul Rashid, Nurul Najwa; Ab Malek, Ezzad; Pahruradzi, Salman; Subano, Muhammad Rizzuan Ariff (Faculty of Computer and Mathematical Sciences, 2023)
Emergencies occur suddenly on public transportation daily. In an emergency, however, there are no explicit means for passengers to submit a report to the LRT authorities. In addition, it is difficult for authorities to discover people in emergency situations, and it takes some time to convey information regarding station and LRT emergencies. With geolocation and decision tree algorithms, this project aims to design and develop an emergency application for LRT passengers. The waterfall approach will be adopted because it is more suitable for this project and will help resolve the issue. Thus, the solution is to design an application capable of sending an immediate report to authorities so that they may simply track down passengers and swiftly notify all users of the emergency in a three station LRT such as Sentul, PWTC and Masjid Jamek. Functional testing to ensure the application works properly.