Please use this identifier to cite or link to this item: http://repository.ipb.ac.id/handle/123456789/165563
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dc.contributor.advisorArhatin, Risti Endriani-
dc.contributor.advisorPanjaitan, James Parlindungan-
dc.contributor.authorBilhaq, Abdillah Yafi-
dc.date.accessioned2025-07-22T03:16:57Z-
dc.date.available2025-07-22T03:16:57Z-
dc.date.issued2025-
dc.identifier.urihttp://repository.ipb.ac.id/handle/123456789/165563-
dc.description.abstractEkosistem mangrove di Desa Blanakan mengalami tekanan akibat konversi lahan dan perubahan iklim yang menyebabkan penurunan luasan vegetasi. Penelitian ini bertujuan memetakan perubahan luasan mangrove secara spasial dan temporal menggunakan citra Sentinel-2A dengan pendekatan Mangrove Vegetation Index (MVI) dan Support Vector Machine (SVM). Data citra tahun 2016 dan 2025 dianalisis melalui tahapan pre-processing, klasifikasi, uji akurasi, dan pengukuran luasan. Hasil menunjukkan bahwa metode MVI memiliki akurasi sebesar 85,7% dengan Kappa coefficient 0,645, sementara metode SVM menunjukkan hasil lebih baik dengan akurasi 93,5% dan Kappa coefficient 0,848. Nilai ambang untuk vegetasi mangrove berkisar antara 2,438 hingga 18,577. Secara kuantitatif, luasan mangrove berdasarkan MVI menyusut dari 187,65 hektar menjadi 60,39 hektar, sedangkan berdasarkan SVM dari 168,96 hektar menjadi 38,81 hektar. Penyusutan ini disebabkan oleh aktivitas antropogenik dan faktor lingkungan, seperti alih fungsi lahan, gelombang laut, serta pencemaran. Temuan ini menegaskan pentingnya teknologi penginderaan jauh sebagai dasar perencanaan konservasi mangrove.-
dc.description.abstractMangrove ecosystems in Blanakan Village are under pressure due to land conversion and climate change, causing a decrease in vegetation area. This study aims to map spatial and temporal changes in mangrove area using Sentinel-2A imagery with the Mangrove Vegetation Index (MVI) and Support Vector Machine (SVM) approach. Image data from 2016 and 2025 were analyzed through the stages of pre-processing, classification, accuracy testing, and area measurement. The results show that the MVI method has an accuracy of 85,7% with a Kappa coefficient of 0,645, while the SVM method shows better results with an accuracy of 93,5% and a Kappa coefficient of 0,848. The threshold values for mangrove vegetation ranged from 2,438 to 18,577. Quantitatively, the mangrove area based on MVI shrank from 187,65 hectares to 60,39 hectares, while based on SVM from 168,96 hectares to 38,81 hectares. This shrinkage was caused by anthropogenic activities and environmental factors, such as land use change, sea waves, and pollution. These findings emphasize the importance of remote sensing technology as a basis for mangrove conservation planning.-
dc.description.sponsorshipnull-
dc.language.isoid-
dc.publisherIPB Universityid
dc.titlePemetaan Perubahan Luasan Mangrove Menggunakan Citra Satelit Multi Temporal di Desa Blanakan, Subang, Jawa Barat.id
dc.title.alternativeMapping Mangrove Area Changes Using Multi-Temporal Satellite Imagery in Blanakan Village, Subang, West Java.-
dc.typeSkripsi-
dc.subject.keywordmangrove/mangrovesid
dc.subject.keywordMVI (Mangrove Vegetation Index)id
dc.subject.keywordMappingid
dc.subject.keywordSubangid
dc.subject.keywordSupport Vector Machines (SVM)id
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