Rheine Aura Shelli Mariska Ardawati, 22314213 (2026) PEMANFAATAN ALGORITMA MACHINE LEARNING UNTUK ANALISIS TANAH PERTANIAN TAHUN 2017 - 2025 PADA WILAYAH PEMBANGUNAN JALAN TOL YOGYAKARTA-BAWEN (Studi Kasus Kalurahan Margokaton, Kapanewon Seyegan dan Kalurahan Tirtoadi, Kapanewon Mlati, Kabupaten Sleman, Daerah Istimewa Yogyakarta). Diploma thesis, Politeknik Agraria STPN.
![[img]](http://repository.stpn.ac.id/style/images/fileicons/text.png) |
Text
Rheine Aura Shelli Mariska Ardawati_22314213.pdf Download (1MB) |
Abstract
The construction of the Yogyakarta–Bawen Toll Road has the potential to impact changes in land use, particularly agricultural land in Margokaton and Tirtoadi Villages. This study aims to determine the extent of land use and changes in agricultural land in 2017, 2020, and 2025 using the Random forest algorithm. This study utilizes Sentinel-2 imagery classified using the Random forest algorithm in QGIS software with the help of Orfeo Toolbox (OTB). Accuracy tests in 2017 and 2020 were conducted using validation data, while in 2025 using data from field checks. Land use change analysis was conducted using the overlay method. The results show that the Random forest algorithm is able to produce land use classification with a good level of accuracy, with Overall Accuracy values ranging from 78.59%–98.02% and Kappa Accuracy values between 70%–96%. Agricultural land dynamics show changes in rice field area in both study areas influenced by regional development and the construction of the Yogyakarta–Bawen Toll Road and increasing built-up area. Keywords: Random forest, Sentinel-2, Agricultural Land, Land Use, Toll Roads
| Item Type: | Thesis (Diploma) |
|---|---|
| Subjects: | H Social Sciences > HD Industries. Land use. Labor > HD29 Pertanahan |
| Divisions: | Prodi Diploma IV Pertanahan |
| Depositing User: | yosep ka perpus |
| Date Deposited: | 18 Sep 2026 08:31 |
| Last Modified: | 18 Sep 2026 08:31 |
| URI: | http://repository.stpn.ac.id/id/eprint/5040 |
Actions (login required)
 |
View Item |
