PEMETAAN HABITAT BENTIK MENGGUNAKAN UNMANNED AERIAL VEHICLE (UAV) DI PERAIRAN PULAU DUA, ENGGANO, BENGKULU

RIFAI, MUHAMMAD ATTAR NOOR and Rozirwan, Rozirwan and Hartoni, Hartoni (2024) PEMETAAN HABITAT BENTIK MENGGUNAKAN UNMANNED AERIAL VEHICLE (UAV) DI PERAIRAN PULAU DUA, ENGGANO, BENGKULU. Undergraduate thesis, Sriwijaya University.

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Abstract

Benthic habitat in the waters of Dua Island, Enggano is the habitat of all aquatic creatures. The use of UAV imagery can be used to see the extent in benthic habitats on Dua Island because UAVs are capable of low flight which allows sensors to observe and collect data. This study aims to map benthic habitat by utilizing UAV imagery and testing the scale and algorithm of Support Vector Machine and Random Forest in classifying benthic habitat on Dua Island. The classification results using Support Vector Machine and Random Forest algorithms on Dua Island produced 4 classes, namely coral reefs, seagrasses, sand and macroalgae. The accuracy value is obtained from the use of a scale of 250 and the Support Vector Machine algorithm with an overall accuracy of 82%. The area of coral reefs is on a scale of 250 and the Support Vector Machine algorithm is 5.3 Ha, seagrass is 3.1 Ha, Sand is 6.1 Ha, and macroalgae is 0.2 Ha. Benthic habitat on the coast of Dua Island, Enggano is able to produce 4 classification classes, where a scale of 250 produces the best classification among other scales and the Support Vector Machine algorithm produces more accurate results than Random Forest. The results of this study can be improved by using more sophisticated tools

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Habitat Bentik, UAV, Pulau Dua, Support Vector Machine, Random Forest
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions:	08-Faculty of Mathematics and Natural Science > 54241-Marine Science (S1)
Depositing User:	Muhammad Attar Noor Rifai
Date Deposited:	18 Jul 2024 06:22
Last Modified:	18 Jul 2024 06:22
URI:	http://repository.unsri.ac.id/id/eprint/151671

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