dc.contributor.advisor | Arhatin, Risti Endriani | |
dc.contributor.advisor | Gaol, Jonson Lumban | |
dc.contributor.author | Azzachra, Syafira | |
dc.date.accessioned | 2024-08-23T07:35:28Z | |
dc.date.available | 2024-08-23T07:35:28Z | |
dc.date.issued | 2024 | |
dc.identifier.uri | http://repository.ipb.ac.id/handle/123456789/158360 | |
dc.description.abstract | Pesisir Kabupaten Cirebon memiliki potensi sumberdaya pesisir seperti ekosistem mangrove, namun kawasan Mangrove di Kabupaten Cirebon diindikasikan telah mengalami kerusakan. Pemantauan mangrove dapat dilakukan melalui teknologi penginderaan jauh menggunakan citra Sentinel-2A. Penelitian ini bertujuan memetakan mangrove dengan membandingkan antara kedua algoritma klasifikasi yaitu Maximum Likelihood (MLH) dan Support Vector Machine (SVM) dengan berbasis piksel. Hasil klasifikasi mangrove dengan algoritma MLH sebesar 13,22 ha, sedangkan untuk algoritma SVM luasnya 9,65 ha. Akurasi yang dihasilkan oleh algoritma MLH dan SVM secara berturut-turut adalah 89,29% dan 91,67%. Luasan sebaran kerapatan mangrove di Desa Mundupesisir, Kabupaten Cirebon dominan oleh kelas rapat dengan luas 9,62 ha menggunakan algoritma SVM. Terdapat korelasi kuat antara tutupan kanopi mangrove dengan nilai NDVI. Sebesar 62,03% variabilitas nilai NDVI dijelaskan oleh persentase tutupan kanopi, sementara sisanya dipengaruhi oleh faktor-faktor lainnya. | |
dc.description.abstract | Cirebon Regency had coastal resources potential with the presence of mangrove ecosystem, however the mangrove area in Cirebon Regency was reportedly experienced damage. Mangrove monitoring can be done through remote sensing technology using Sentinel-2A imagery. This research aimed to map mangroves by comparing two classification algorithms, namely Maximum Likelihood (MLH) and pixel-based Support Vector Machine (SVM). The mangrove classification results using the MLH algorithm was 13.22 ha, while for the SVM algorithm the area was 9.65 ha. The accuracy produced by the MLH and SVM algorithms were 89.29% and 91.67% respectively. The distribution area of mangrove density in Mundupesisir Village, Cirebon Regency was dominant in the dense class with an area of 9.62 ha using the SVM algorithm. There was a strong correlation between mangrove canopy cover and NDVI values. 62.03% of the variability in NDVI values was explained by the percentage of canopy cover, while the rest influenced by other factors. | |
dc.description.sponsorship | | |
dc.language.iso | id | |
dc.publisher | IPB University | id |
dc.title | Pemetaan Luasan dan Kerapatan Mangrove di Desa Mundupesisir, Kabupaten Cirebon, Jawa Barat | id |
dc.title.alternative | | |
dc.type | Skripsi | |
dc.subject.keyword | mangrove | id |
dc.subject.keyword | SVM | id |
dc.subject.keyword | sentinel-2A | id |
dc.subject.keyword | Mundupesisir Village | id |
dc.subject.keyword | MLH | id |