Identifikasi kecakapan inovasi lembaga riset di Indonesia berbasis dokumen

Introduction. Duplication in inventions produced by research institutions in Indonesia becomes an issue. It is important to map the specialization of the invention in research institutions. This study examines  the mapping of the innovation in research institutions in Indonesia. Data Collection Method. This study uses a patent-based technology document analysis method to map the potential of technology. The data used is patent data registered in the Direktorat Jenderal Kekayaan Intelektual (DJKI) database. Data Analysis. Metadata analysis was conducted by using the K-Means Klastering method with R software. Results and Discussions. The findings in the pre-analysis show that when the independent variable involved in the model are very large, the Localized feature selection method can effectively select variables without losing much information. There are 5 dominant technology groups that can be produced by research institutions in Indonesia, namely 1) Technology related to the development of measurement and testing instrument technology; 2) Technologies related to food and food ingredients; and 3) microstructural test equipment / detectors; 4) radar technology; 5) Technology in agriculture. Conclusion. The findings show that there are still overlapping inventions by several research institutions in the same technology cluster. K-means clustering with LFSBSS pre analysis has a clear performance in the technology cluster space.