RANCANGAN CHATBOT REKOMENDASI COFFEE SHOP JABODETABEK DENGAN MENGGUNAKAN DIALOGFLOW NATURAL LANGUAGE PROCESSING
Abstract
Public interest in coffee culture is increasing, especially in the JABODETABEK area. Some ways to get information about finding recommendations for coffee shops that are tiring through social media platforms, asking peers, advertisements and others still feel less effective and efficient. Utilization of chatbot technology and Natural Language Processing as an effective solution in providing coffee shop recommendations to users. This research aims to design and implement a chatbot that has the ability to deliver coffee shop recommendations based on user preferences. This chatbot is applied with Dialogflow which is able to connect to the Telegram platform. Dialogflow is used to process user input in the form of natural language and provide additional information such as location, opening hours, prices, menus, and social media to communicate to the coffee shop. Chatbot is a practical way for Telegram users to communicate information quickly. The expected result of this coffee shop recommendation chatbot system using Dialogflow NLP is to be able to provide useful and relevant recommendations to users, with the potential to promote coffee culture in the Jabodetabek area.
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References
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