impermeable layers can trigger slippage, leading to
landslides (Paimin et al., 2009).
Another determining factor for landslide occurrences
in the study area is land use, which relates to the land's
ability to respond to water. Landslides commonly
occur on agricultural lands, such as fields and dryland
farms. The incidence of landslides increases with the
rapid change in land use in this region, as Garut
Regency is among the areas with a high rate of land-
use change, especially around slopes and the foothills
of volcanic mountains, which are fertile for
horticulture or seasonal crops like corn, cabbage,
scallions, and other vegetables (Muldiana et al.,
2016). Intensive land-use changes, driven by
infrastructure development or agricultural expansion,
can increase landslide potential (Moresi et al., 2020;
Pasang & Kubicek, 2020). Agricultural activities in
Garut Regency occur on various topographies, with
dryland farming spread across hills and the foothills
to the slopes of mountains, including areas with
slopes > 25%. This situation disrupts soil stability and
potentially increases landslide occurrences
(Anbalagan et al., 2015). The type of land use affects
slope stability, as seasonal agricultural lands with
shallow-rooted crops decrease slope stability,
increasing the risk of landslides (Susanti & Miardini,
2019). Landslide events in Garut Regency primarily
occur on slopes > 25%, with land uses such as
plantations, fields, and shrublands.
4 CONCLUSIONS
The study produced several conclusions:
1. The use of GIS and the CMA model
effectively maps landslide hazard areas by
comparing five determining parameters with
the landslide occurrence parameter through
weighting and scoring of each parameter.
2. Geological factors, land use, and slope are
the parameters with the highest contribution
to landslide occurrences in Garut Regency.
3. The distribution of high and very high
landslide hazard areas is generally located in
the southern to central parts of Garut
Regency, which consist of a series of hills
and mountains, primarily in Cisompet and
Pakenjen Districts. Areas classified as
relatively non-hazardous to slightly
hazardous are typically found in the central
to northern and western regions, which have
gentler slopes, including Garut Kota,
Tarogong Kidul, Tarogong Kaler, and
Banyuresmi Districts.
RECOMMENDATIONS
The resulting landslide hazard map can serve as a
consideration in spatial planning as an initial step to
determine the type and location of land use allocation
as part of landslide disaster mitigation efforts in the
Garut Regency. For future research, the use of the
CMA model and GIS relies heavily on the number
and types of parameters applied. Additional
parameters should be included to obtain improved
results.
REFERENCES
Anbalagan, R., Kumar, R., Lakshmanan, K., Parida, S., &
Neethu, S. (2015). Landslide hazard zonation mapping
using frequency ratio and fuzzy logic approach , a case
study of Lachung Valley , Sikkim. Geoenvironmental
Disasters, 2(6), 1–17. https://doi.org/10.1186/s40677-
014-0009-y
Boonyanuphap, J., Suratmo, F. G., & Jaya, I. N. S. (2001).
Gis-based method in developing wildfire risk model
(Case study in Sasamba, East Kalimantan, Indonesia).
Jurnal Manajemen Hutan Tropika, 7(2), 33–45.
https://doi.org/10.7226/jmht.7.2.
Faizana, F., Nugraha, A. L., & Yuwono, B. D. (2015).
Pemetaan risiko bencana tanah longsor Kota Semarang.
Jurnal Geodesi Undip, 4(1), 223–234.
Haryani, N. S., Zubaidah, A., Dirgahayu, D., Hidayat, F. Y.,
& Junita, P. (2012). Model bahaya banjir menggunakan
data penginderaan jauh di Kabupaten Sampang. Jurnal
Penginderaan Jauh, 9(1), 52–66.
Mersha, T., & Meten, M. (2020). GIS-based landslide
susceptibility mapping and assessment using bivariate
statistical methods in Simada area , northwestern.
Moresi, F. V., Maesano, M., Collalti, A., Sidle, R. C.,
Matteucci, G., & Mugnozza, G. S. (2020). Mapping
Landslide Prediction through a GIS-Based Model : A
Case Study in a Catchment in Southern Italy.
Geosciences, 10(309), 1–22.
https://doi.org/doi:10.3390/geosciences10080309
Mubekti, M., & Fauziah, A. (2008). Mitigasi Daerah Rawan
Tanah Longsor Menggunakan Teknik Pemodelan
Sistem Informasi Geografis; Studi Kasus: Kecamatan
Sumedang Utara dan Sumedang Selatan. Jurnal Teknik
Lingkungan, 9(2), 121–129.
Muldiana, A., Sugandi, D., & Somantri, L. (2016).
Pemanfaatan citra landsat 8 untuk analisis penggunaan
lahan di Kabupaten Garut. Antologi Pendidikan
Geografi, 4(2), 73–80.
http://journal.ikippgriptk.ac.id/index.php/edukasi/articl
e/download/17/16
Paimin, Sukresno, & Pramono, I. B. (2009). Teknik Mitigasi
Banjir dan Tanah longsor (A. N. Ginting (ed.)).
Tropenbos International Indonesia Programme.
Pasang, S., & Kubicek, P. (2020). Landslide Susceptibility
Mapping Using Statistical Methods along the Asian