This research focuses on enhancing transparency in search results. By incorporating interpretable algorithms, we aim to provide users with clear insights into how information is retrieved, fostering trust and empowering users to understand and evaluate the relevance of search outcomes more effectively.
In this innovative project, we integrate social media sensing with fire spread modelling. We aim to enhance early fire detection and prediction by harnessing real-time data from social platforms. This interdisciplinary approach combines cutting-edge technology with environmental science, fostering a proactive strategy for wildfire management and community safety.
1) Machine Learning and Social Media Harvesting for Wildfire Prevention
AD Laksito, K Kusrini, A Setyanto, MZF Johari, ZR Maruf, KA Yuana, et al.
2023 IEEE 13th International Conference on Pattern Recognition Systems (ICPRS)
2) Monte Carlo method for map area calculation in wildland fire map management
Kumara Ari Yuana, Arief Setyanto, Arif Dwi Laksito, Zauvik Rizaldi Maruf, et al.
2022 6th International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE)