The Combination of Natural Language Processing and Entity Extraction for Academic Chatbot

At ISB Atma Luhur, there is a web application specifically for students in accessing academic information in which the usage is good enough, but felt less practical and effective. After logged in, a student must provide some input, such as clicking on buttons and menus to display academic information. This web application interface is felt too small if opened by using a mobile browser that causes some students to experience difficulty in tapping buttons or menus. The solution that can be offered to overcome this problem is to use an Android-based chatbot. The chatbot can simplify the process of accessing information, i.e., by chatting on chatbot application and its interface size is adjusted according to the user device. The used model, method, and software development tools, respectively, are prototype models, object-oriented methods, and UML (Unified Modeling Language). The created chatbot apply NLP (Natural Language Processing) algorithm and entity extraction method, so that chatbot can respond appropriately and according to requests from students. The created chatbot makes the academic information at ISB Atma Luhur can be accessed easily, quickly, and efficiently by students without having to zoom in and zoom out.