Estimation of Potassium Content in Salak Plants Using Green Normalized Difference Vegetation Index Method in Wonokerto Village, Turi, Sleman, Yogyakarta: Estimasi Kandungan Kalium pada Tanaman Salak Menggunakan Metode Green Normalized Difference Vegetation Index di Kalurahan Wonokerto, Turi, Sleman, Yogyakarta - Ramadhani Muhammad Yusuf Ardiansyah; Virgawati, Sari (Universitas Pembangunan Nasional Veteran Yogyakarta, 2025)
Salak (Salacca zalacca) is a major horticultural crop in Sleman Regency, Yogyakarta, yet recent years have seen a decline in its productivity, potentially due to potassium (K) deficiency. This study aims to estimate potassium content in Salak plant tissues using the Green Normalized Difference Vegetation Index (GNDVI) derived from Sentinel-2 satellite imagery and to evaluate the accuracy of this approach against laboratory-based measurements. The research was conducted in Wonokerto Village, Turi District, Sleman Regency, employing a quantitative descriptive method. A total of 30 sampling points were selected, comprising 20 prediction points and 10 reference points. GNDVI values were extracted through Sentinel-2 image processing using ArcGIS software, while potassium content in leaf tissue was determined via the wet digestion method using HNO₃ and HClO₄. Leaf samples were collected from the central part of the midrib, serving as a physiological indicator of plant nutrient status. Statistical analyses included Pearson’s correlation, linear regression, paired sample t-test, and Root Mean Square Error (RMSE) assessment. The findings revealed a correlation coefficient (r) of 0.604, indicating a strong positive relationship between GNDVI and potassium content. The regression analysis showed no significant difference between predicted and observed values, while the RMSE value of 0.19445 suggested a low prediction error. These results demonstrate that GNDVI has strong potential as a non-destructive, efficient, and cost-effective tool for estimating potassium levels in Salak plant tissues. The resulting prediction map can be applied to support more precise potassium fertilization strategies in Salak cultivation within the study area.