A Tracer Study Design With Whatsapp Chatbot Integration Using Natural Language Processing - Firdaus, Wigananda (Information Technology International Journal, 2024)
Tracer study is a method used by educational institutions to track alumni and assess the effectiveness of the education provided. A key challenge in conducting these studies is the low participation rate of respondents, often due to lengthy surveys and a lack of interactive engagement. To address this issue, a WhatsApp chatbot system powered by Natural Language Processing (NLP) was developed. This system facilitates an interactive and user-friendly survey experience, allowing respondents to complete the survey directly through WhatsApp without needing to visit a website. Responses are automatically stored in Google Sheets via an API. By using a microservices architecture, the project efficiently separates crucial components such as WhatsApp API, NLP services, and Google Sheets API, leading to improved data collection efficiency and a more convenient survey process for respondents.