Tuberculosis (TB) remains a major public health problem in Indonesia, ranking third worldwide in case numbers. The Indonesian government has strengthened case detection strategies, including the Active Case Finding (ACF) program; however, its implementation still faces challenges due to paper-based workflows that cause delays, duplicate data, and weak integration. This study aimed to design a conceptual model of a web-based information system to improve the efficiency, accuracy, and monitoring capacity of ACF. A descriptive observational design with mixed methods was applied, involving TB patients and healthcare workers selected purposively. Data were collected through questionnaires and focus group discussions (FGDs) to identify barriers and system requirements. The findings showed that the total performance score across six ACF stations was 63.89% (fair), highlighting critical issues in manual data handling. Based on these findings, a web-based system model was proposed, featuring online registration, SITB synchronization, and WhatsApp integration for patient follow-up. The model demonstrates potential to reduce administrative burden, support real-time monitoring, and accelerate diagnosis and treatment, while serving as a strategic foundation for digital health policies and TB elimination efforts in Indonesia.

Tuberculosis, ACF, Digital Health, Web-based System