Pemetaan Luasan dan Kerapatan Mangrove di Desa Pantai Bahagia, Kecamatan Muara Gembong, Kabupaten Bekasi

Abstract

Penurunan luasan mangrove menyebabkan perlunya pemantauan hutan mangrove untuk mencegah terjadinya dampak keberlanjutan dari degradasi lahan mangrove di pesisir Desa Pantai Bahagia, Kecamatan Muara Gembong, Kabupaten Bekasi. Penelitian ini bertujuan mengidentifikasi dan memetakan luas sebaran dan kerapatan mangrove di Desa Pantai Bahagia. Analisis Normalized Difference Vegetation Index (NDVI) digunakan untuk mengetahui kerapatan mangrove di suatu area. Kerapatan mangrove yang dihasilkan terklasifikasi menjadi 3 kelas kerapatan, yaitu mangrove jarang (0,693 km2), mangrove sedang (0,562 km2), dan mangrove rapat (1,865 km2) dengan total luasan mangrove sebesar 3,12 km2. Hasil uji akurasi confusion matrix pada klasifikasi citra memperoleh nilai akurasi sebesar 86,58% dan kappa coefficient sebesar 0,697. Pengujian korelasi persentase tutupan kanopi mangrove yang diperoleh dari data lapang dengan nilai NDVI dilakukan menggunakan metode regresi linier sederhana dan menghasilkan koefisien korelasi (r) dengan nilai 0,834 dan koefisien determinasi (R2) dengan nilai 0,696.

Mangrove areas decreasing lead to the need for monitoring of mangrove forests to prevent the impacts of mangrove area degredation that occured in the coast of Pantai Bahagia Village, Muara Gembong District, Bekasi Regency. This research aimed to compute and make distribution area and density map of mangrove in Pantai Bahagia Village. Normalized Difference Vegetation Index (NDVI) analysis is used to determine the density of mangroves in certain area. The results were classified into 3 classes, sparse (0,693 km2), moderate (0,562 km2), and dense (1,865 km2) with a total mangrove area of 3,12 km2. The confusion matrix accuracy test results were consisted with an accuracy value of 86.58% and kappa coefficient of 0.697. The correlation test of mangrove canopy cover percentage obtained from field data with NDVI value was conducted using a simple linear regression method. The results were 0.834 for coefficient of correlation (r) and 0.696 for coefficient of determination (R2).