Indah Amallia Fitri
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Integrasi SIG Dan Penginderaan Jauh Untuk Pemetaan Kesehatan Perkebunan Kelapa Sawit: Studi Kasus: Kecamatan Sangir Balai Janggo, Kabupaten Solok Selatan, Sumatera Barat Indah Amallia Fitri; Dwi Arini; Fajrin Fajrin
Jurnal Sains dan Ilmu Terapan Vol. 8 No. 1 (2025): Jurnal Sains dan Ilmu Terapan
Publisher : Politeknik Kampar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59061/jsit.v8i1.922

Abstract

Sangir Balai Janggo District has many productive oil palm plantations, making it an ideal location for research related to oil palm plant health. Oil palm is a major commodity in Indonesian plantations, so mapping its health is crucial for sustainable agricultural management. This study aims to analyze the health of oil palm plants using the integration of Geographic Information Systems (GIS) and Remote Sensing with the Normalized Difference Vegetation Index (NDVI) method based on Sentinel-2A imagery. The results of the study show that the health of oil palm plants in Sangir Balai Janggo District is divided into four categories: very healthy (26,967.40 Ha; NDVI 0.66-0.87), fairly healthy (3,228.31 Ha; NDVI 0.33-0.66), unhealthy (547.75 Ha; NDVI 0-0.33), and dead (10.53 Ha; NDVI -0.33 - 0). The total area of oil palm plantations reaches 30,753.62 Ha. This study demonstrates that the integration of GIS and remote sensing is highly effective in accurately and efficiently mapping the health condition of oil palm plantations.