DEVELOPMENT OF FILTERING FEATURE IN METAVERSE MIND MAP WITH VIRTUAL REALITY TECHNOLOGY

• Main Author: Lukman, Maximillian
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/74533
• Institution: Institut Teknologi Bandung

Over the past decade, technology has brought about significant changes in human life. One prominent application of technology in recent years is online learning systems. However, online learning still faces effectiveness challenges due to various learning obstacles experienced by students. Therefore, there is a need to develop a learning medium, such as a mind map application, utilizing virtual reality technology in the Metaverse. Considering the vast array of learning materials, there may be highly complex topics that require a feature to assist users in searching for information within intricate mind maps. The objective of this Final Project is to create a filtering feature for the mind map application in the Metaverse. The filtering feature encompasses three main processes: data retrieval and segmentation, search or filtering process, and visualization. The first process involves retrieving and segmenting the entire mind map data into smaller fragments to facilitate the search process. The search or filtering process serves as the primary mechanism, utilizing the OpenAI model to find relevant information within the mind map data or from external sources. The final process, visualization, aims to present the search or filtering results in a visual format on the mind map. Testing is conducted to evaluate the efficiency, effectiveness, and relevance of the implemented mind map application in the Metaverse, including the filtering feature. Creating mind maps using the application demonstrates slightly improved effectiveness compared to traditional handwritten mind maps. Furthermore, with the filtering feature, information retrieval by users in the application may be slower, but in terms of relevance, the use of the filtering feature yields satisfactory results compared to information retrieval without the filtering feature.