Temporal and Spatial Analysis of Vegetation and Non-Vegetation Using Landsat 8 Imagery with a Support Vector Machine Approach - Syifa Fauziyah; Fauzan, Achmad (EKSAKTA: Journal of Sciences and Data Analysis, 2025)
Kertajati International Airport is one of the newest airports located in Majalengka regency, West Java province. The establishment of this airport has sparked interest as a case study, particularly regarding land-use changes around the Kertajati area and, more broadly, in Majalengka Regency. This study aims to measure the extent of changes in vegetated and non-vegetated land around Kertajati International Airport, Majalengka Regency, West Java Province. The methodology employed involves the Support Vector Machine (SVM) classification method. Various kernels, including (1) linear, (2) polynomial, (3) radial basis function (RBF), and (4) sigmoid, were simulated in the analysis. The data used in this study comprise Landsat 8 satellite imagery obtained from Google Earth Engine, utilizing bands such as red, green, blue, near-infrared (NIR), and shortwave infrared (SWIR) for the years 2013 and 2023. The dataset was split using the hold-out method into four scenarios, with varying training and testing data proportions: 75%-25%, 80%-20%, 85%-15%, and 90%-10%. Each scenario was repeated 40 times to ensure robust results. The best results were achieved using the SVM model with an RBF kernel at a data split ratio of 75%-25%, as indicated by the highest accuracy scores. Consistent with the accuracy, the evaluation metrics also fell into a high-performance category. Land area predictions for the vicinity of Kertajati International Airport were analyzed based on the optimal data split proportion. The results of this study reveal a significant reduction in vegetated land from 2013 to 2023, accompanied by a notable increase in non-vegetated land over the same period.