Forward Chaining Method Implementation for AI-Powered Passenger Ojek Online and Drive Solutions

Abstract

This research explores the application of artificial intelligence (AI)-based technology in the Grab application, an online passenger transportation service company in Southeast Asia. The main aim of this research is to improve service quality, safety and efficiency for Grab passengers and drivers, while solving traffic and location problems. The use of AI in this application opens up opportunities to optimize passenger pick-up and drop-off processes, improve navigation, and improve real-time traffic management. Special emphasis is placed on the application of the Forward Chaining method, an artificial intelligence technique that allows systems to make decisions based on predetermined rules. By implementing this method, Grab can predict passenger movements and arrange the best routes automatically, increasing time efficiency and reducing congestion. The implications of this research are very significant in the context of improving the quality of online transportation services, by providing a better experience for passengers and ensuring safety on every trip. The main contribution of this research is the development of an efficient and reliable AI system, as well as the application of Forward Chaining in the context of the Grab application. Additionally, this research provides an in-depth understanding of how AI technology can overcome traffic and location challenges, creating effective and reliable solutions for ride-hailing companies in the future. The results of this research provide a valuable contribution to the development of transportation technology, providing a basis for similar companies to explore the potential of applying artificial intelligence in their services. Thus, this research paves the way to greater innovation in the field of online transportation, creating a more efficient, safe and comfortable environment for users, and creating significant added value for the industry.