Performance Analysis of QGIS Plugin for Landslide Hazard Index Preparation - Amirul Dewa Rizkya; Heri Priyanto; Morteza Muthahhari (Jurnal Multidisiplin Indonesia, 2026)
Landslides are a significant threat in Indonesia, with major impacts on social, economic, and infrastructure aspects. One important mitigation measure is the development of landslide hazard index maps. However, conventional methods using proprietary software such as ArcGIS or manual processing in QGIS are time-consuming and prone to technical errors. This study analyzes the performance of a QGIS plugin developed to accelerate and simplify the process of generating landslide hazard indices. The plugin was built using the Python programming language, GDAL and Rasterio spatial libraries, and an interface designed with QtDesigner through a Rapid Application Development (RAD) approach. Performance analysis was conducted by comparing processing duration and output consistency between the conventional method and the plugin. The test data included a Digital Elevation Model (DEM), Landslide Susceptibility Map (ZKGT), and administrative boundaries of Sanggau Regency. The results showed that the plugin reduced processing time from 410 seconds to 280 seconds while producing hazard index maps consistent with the manual method. In addition, the plugin reduced the risk of user errors in repetitive stages, such as reclassification and raster calculations. In conclusion, the developed QGIS plugin improves efficiency and reliability in landslide hazard index mapping. This performance analysis confirms that the plugin can serve as an effective open-source solution for disaster mitigation and reduce dependence on commercial software.