A Systematic Literature Review on Chatbot Development For Whatsapp: Programming Language, Method, And Utility - Rahulil, Muhammad; Yuni Yamasari; Ricky Eka Putra; I Made Suartana; Anita Qoiriah (Jurnal Serambi Engineering, 2025)
The development of chatbot technology in recent years has shown rapid advancements across various sectors, particularly on popular communication platforms such as WhatsApp. A systematic review is necessary to identify advancements related to chatbot development on WhatsApp. Therefore, this study presents a systematic literature re-view on the development and use of WhatsApp chatbots using the PRISMA framework. From an initial search of 41 studies, followed by filtering according to categories, eight relevant articles were identified from various digital data-bases through focused searches using the keyword "WhatsApp chatbot". The review results indicate that Natural Language Processing (NLP) methods are the most commonly applied approach in chatbot development, with Python being the dominant programming language. This is attributed to Python's flexibility and strong library support, such as NLTK, spacy, and TensorFlow, which enable more efficient chatbot development. The findings reveal that WhatsApp chatbots have been applied in various sectors, including healthcare, business, and education. The study's outcomes highlight the challenges and opportunities in future chatbot development, such as the integration of additional features and the enhancement of conversational context understanding. By providing in depth insights into trends and best practices, this study contributes to the development of WhatsApp chatbots as increasingly relevant and effective automated communication tools.