LEO RASTRA PRATAMA, 22314375 (2026) PREDIKSI PERUBAHAN PENGGUNAAN TANAH TAHUN 2030 MENGGUNAKAN METODE CELLULAR AUTOMATA (CA) DI KABUPATEN NGAWI. Diploma thesis, Politeknik Agraria STPN.
![[img]](http://repository.stpn.ac.id/style/images/fileicons/text.png) |
Text
Leo Rastra Pratama_22314375.pdf Download (1MB) |
Abstract
Land use change is a dynamic process driven by population growth, infrastructure development, and economic activities, resulting in continuous spatial transformation. Information on future land use changes is essential to support sustainable spatial planning. This study aims to (1) analyze land use changes in Ngawi Regency from 2015 to 2020, (2) identify the spatial factors influencing land use change, and (3) predict land use conditions in 2030 using the Cellular Automata–Artificial Neural Network (CA-ANN) model. This research employed a quantitative spatial approach using Landsat 8 imagery from 2015, 2020, and 2025. Land use classification was conducted using the Supervised Maximum Likelihood Classification method, while land use changes were analyzed through overlay techniques in ArcGIS. Logistic regression analysis was applied to evaluate the influence of spatial driving factors, including distance to roads, industrial areas, educational facilities, health facilities, and commercial centers. Land use prediction was performed using the MOLUSCE plugin in QGIS. The results indicate that during the 2015–2020 period, settlement areas increased by 2,305.62 ha, agricultural land by 281.25 ha, and open land by 15.30 ha, whereas forest areas decreased by 2,504.88 ha and inland water bodies by 97.29 ha. Logistic regression analysis revealed that distance to roads, industrial areas, educational facilities, and commercial centers significantly influenced land use change, while distance to health facilities had no significant effect. The CA-ANN model achieved 90.35% Correctness with an Overall Kappa value of 0.84948, indicating good predictive performance. The 2030 prediction suggests that agricultural land will remain the dominant land use, covering 64,788.21 ha (46.45%), followed by forests with 41,418.36 ha (29.70%) and settlements with 31,874.85 ha (22.85%). Future settlement expansion is predicted to follow major transportation corridors and activity centers, while Ngawi Regency is expected to maintain its predominantly agricultural character through 2030. Keywords: land use change, Cellular Automata, CA–ANN, spatial prediction, Ngawi Regency.
| 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: | 30 Oct 2026 08:24 |
| Last Modified: | 30 Oct 2026 08:24 |
| URI: | http://repository.stpn.ac.id/id/eprint/5303 |
Actions (login required)
 |
View Item |
