Sabila Rafani Aliandra, . (2022) PENERAPAN METODE GABOR WAVELETS DAN MEDIAN FILTER UNTUK KLASIFIKASI POHON KELAPA SAWIT PADA DATA CITRA LIDAR. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
![[img]](http://repository.upnvj.ac.id/style/images/fileicons/text.png) |
Text
ABSTRAK.pdf Download (15kB) |
|
Text
AWAL.pdf Download (793kB) |
|
Text
BAB I.pdf Download (25kB) |
|
Text
BAB II.pdf Restricted to Repository UPNVJ Only Download (268kB) |
|
Text
BAB III.pdf Restricted to Repository UPNVJ Only Download (413kB) |
|
Text
BAB IV.pdf Restricted to Repository UPNVJ Only Download (786kB) |
|
Text
BAB V.pdf Download (68kB) |
|
Text
DAFTAR PUSTAKA.pdf Download (77kB) |
|
Text
DAFTAR RIWAYAT HIDUP.pdf Restricted to Repository UPNVJ Only Download (31kB) |
|
Text
LAMPIRAN.pdf Restricted to Repository UPNVJ Only Download (724kB) |
|
Text
ARTIKEL KI.pdf Restricted to Repository staff only Download (829kB) |
Abstract
The palm oil industry in Indonesia is demanded to be more productive and efficient. This study focuses on the problem of implementing algorithmic computational methods in digital image processing using machine learning technology that can be used as strategic tools in the process of maintaining and monitoring oil palm plantations. The purpose of this study was to determine the effectiveness of the application of the Median Filter and Gabor Wavelets method in classifying oil palm trees on LiDAR image data. A Median Filter that is able to remove salt and pepper noise in the image can help improve the quality of image clarity. Meanwhile, Gabor Wavelets which are very popular in digital image processing as a feature extraction method/texture features are expected to be able to select important features for the classification process. As a result, the Median Filter cannot significantly affect the classification results, because the image data does not contain a lot of salt and pepper noise. However, the image data processed by the Median Filter provides the highest accuracy and F1-score among other experiments in this study, which are 84.98% and 0.85093. On the other hand, Gabor Wavelets can affect the classification results, but still cannot improve accuracy and F1-score compared to the research.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No.Panggil: 1810511088] [Pembimbing: Desta Sandya Prasvita] [Penguji 1: Yuni Widiastiwi] [Penguji 2: Mayanda Mega Santoni] |
| Uncontrolled Keywords: | Median Filter, Gabor Wavelets, LiDAR, classification, palm tree |
| 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: | Sabila Rafani Aliandra |
| Date Deposited: | 01 Aug 2022 07:09 |
| Last Modified: | 01 Aug 2022 07:09 |
| URI: | http://repository.upnvj.ac.id/id/eprint/19544 |
Actions (login required)
 |
View Item |