Pemetaan Daerah Rawan Longsor Menggunakan Machine Learning di Kecamatan Muara Tami, Kota Jayapura, Papua - M Aldi; Indra Rivaldi Siregar; Alissa Bilqis (Jurnal Geofisika, 2021)
One of the high landslide vulnerability areas in Indonesia is located in Muara Tami District, Jayapura City. The main factors triggering the landslide are steep slopes and high elevations. However, there are still several other factors that also influence the occurrence of landslides, such as vegetation, land cover, and curvature. Landslides that occur can cause damages to all parties, both material and non-material. Therefore, it is necessary to map landslide-prone areas as a non-structural mitigation planning. This planning is useful for identifying areas that are relatively safer from landslides so that the fatalities incurred can be minimized. In this mapping, several parameters are used that are thought to trigger landslides, then they are calculated by machine learning using the random forest method. Based on the parameters used, the eastern and northwestern areas have high slope and elevation values, high curvature contrast values, and dry land forest cover. These results indicate the high potential for landslide vulnerability in both parts of the study area. Meanwhile, areas with low potential for landslide vulnerability have a curvature of 0, a relatively low slope and elevation. The model accuracy value obtained by the random forest method is 0.9. This value is categorized as good enough because it shows that the parameters used are good enough in mapping landslide vulnerability in the study area. These results are also supported by the high sensitivity and specificity values ​​based on the ROC curve. Areas with high potential for landslide vulnerability are Mosso Village and the border between Skow Mabo, Skow Yambe, Koya Tengah, Koya Timur, and Holtekam. Meanwhile, areas with low landslide potential were Skow Sae Village, the central part of East Koya, the northern part of West Koya, and the southern part of Holtekam.