IoT-Based Digital Twin Dashboard for Mushroom Cultivation Monitoring Using a Cloud-Based Data Visualization Platform

Oyster mushroom cultivation is an agricultural sector that is sensitive to changes in temperature and humidity. However, at the MSME level, environmental monitoring is still mostly done manually with intuition, making it prone to errors and decreasing its productivity. This research aims to develop an IoT-based monitoring system visualized through a twin digital dashboard using the Looker Studio cloud-based platform. The system is built with DHT11 and Raspberry Pi sensors that send temperature and humidity data to a cloud database and display it in a dashboard that can be accessed remotely with an update interval every 10 minutes. Usability evaluation was conducted using the PSSUQ instrument which includes three dimensions, namely System Usefulness, Information Quality, and Interface Quality. The evaluation results showed an excellent score with an overall average of 1.63, reflecting ease of use, information quality, and system suitability to the needs of non-technical users. Unlike previous studies that relied on closed or paid platforms, this system offers an open, free, and easily customizable solution. The main contribution of this research is in addressing the challenges of limited technology and digital literacy of MSMEs by providing an inclusive, efficient, and contextual visualization approach for the small-scale agriculture sector.