Imha luchman, . (2022) KLASIFIKASI POHON KELAPA SAWIT MENGGUNAKAN CITRA LIDAR DENGAN CONVOLUTIONAL NEURAL NETWORK. Tugas Akhir thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
Palm oil is one of the most important commodities in the world, this is because palm oil can be processed into palm oil which has high economic value. Indonesia as the largest producer of palm oil in the world has an area of up to 16 million hectares of oil palm plantations. Extensive oil palm plantations can give rise to various environmental problems such as deforestation for land acquisition or the destruction of forest ecosystems. With the combination of the convolutional neural network image classification method on remote sensing LiDAR data, we can classify oil palm trees on large plantations remotely so that we can determine the efficiency level of resource and land use in oil palm plantations. This study uses remote sensing data LiDAR on oil palm plantations in Kalimantan was obtained from PT Pudjiastuti Geosurvey. In this research, the highest accuracy is obtained up to 98% and validation accuracy is up to 86%.
| Item Type: | Thesis (Tugas Akhir) |
|---|---|
| Additional Information: | [No.Panggil: 1710511040] [Pembimbing 1: Theresia Wati] [Pembimbing 2: Desta Sandya Prasvitai] [Penguji 1: Yuni Widiastiwi] [Penguji 2: Mayanda Mega Santoni] |
| Uncontrolled Keywords: | Palm oil, Convolutional neural network, Remote Sensing |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Informatika (S1) |
| Depositing User: | Imha Luchman |
| Date Deposited: | 08 Mar 2022 07:28 |
| Last Modified: | 08 Mar 2022 07:28 |
| URI: | http://repository.upnvj.ac.id/id/eprint/16476 |
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