Enhancing Field Activity Reporting through a Real-Time Telegram Chatbot Integrated with the Google Sheets API - Nabila, Khansa; Abdulmajid, Nuur Wachid (Integrated Science Education Journal, 2026)
Purpose of the study: This study aims to design and develop a Telegram chatbot integrated with the Google Sheets API as a smart evidence reporting solution to improve the efficiency, accuracy, and timeliness of field activity reporting. Methodology: This study employed the Design Thinking approach as a user-centered system development method, consisting of five stages: empathize, define, ideate, prototype, and test. Data were collected through observations and interviews with staff involved in the field activity. A Telegram chatbot prototype was developed using the Telegram Bot API and integrated with Google Sheets through Google Apps Script. System evaluation was conducted using Black Box Testing to assess functionality and User Acceptance Testing (UAT) to measure user perception and acceptance. Main Findings: The results show that the developed chatbot system functions effectively as a smart evidence reporting tool. The integration enables real-time, automated, and structured storage of field activity data in Google Sheets. Black Box Testing confirmed that all system functions operated as expected, while User Acceptance Testing indicated a high level of user satisfaction, with an acceptance rate of 88%. The chatbot successfully supports fast data input, reduces reporting errors, and improves operational efficiency during field activities. Novelty/Originality of this study: The novelty of this study lies in the use of a widely adopted messaging platform as the primary interface for structured field activity reporting. By leveraging Telegram as a conversational interface and integrating it directly with cloud-based data storage, this study presents a lightweight, low-cost, and easily deployable reporting solution.