Landslide Hazard Analysis Based on Geographic Information Systems in Sumedang Regency

Authors

Rakhmad Fadillah , Boedi Tjahjono , Fifi Gus Dwiyanti

DOI:

10.29303/jppipa.v10iSpecialIssue.8354

Published:

2024-08-25

Issue:

Vol. 10 No. SpecialIssue (2024): Science Education, Ecotourism, Health Science

Keywords:

Hazard, Disaster, Landslide, Mitigation

Research Articles

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Fadillah, R., Tjahjono, B., & Dwiyanti, F. G. (2024). Landslide Hazard Analysis Based on Geographic Information Systems in Sumedang Regency. Jurnal Penelitian Pendidikan IPA, 10(SpecialIssue), 147–158. https://doi.org/10.29303/jppipa.v10iSpecialIssue.8354
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Abstract

Sumedang Regency has a hilly landscape, making it one of the 13 cities/regencies in West Java Province that are prone to landslides. A total of 80 landslide incidents were recorded from 2019 to 2023. These landslides resulted in 45 fatalities, 53 injuries, and damage to 317 infrastructure units. This situation indicates the importance of conducting an analysis of landslide hazard distribution. The landslide hazard distribution analysis is carried out using a weighting and scoring method on the parameters used, which include: slope gradient, rainfall, actual land cover, landform, lithology, and soil type. Based on these parameters, four landslide hazard classes were identified in Sumedang Regency: low, medium, high, and very high hazard classes. Proportions of these hazard are as follows: high hazard class (42.24%), medium hazard class (40.38%), low hazard class (13.90%), and very high hazard class (3.49%). The low hazard class is mainly found in the northern part of Sumedang Regency, the medium hazard class is widespread in sloping areas, and the high to very high hazard classes are primarily found in the Tampomas mountains and areas with hilly landforms. Slope gradient and rainfall are the factors that most influence landslide hazards, making it necessary to design appropriate mitigation.

References

Abbaszadeh Shahri, A., Spross, J., Johansson, F., & Larsson, S. (2019). Landslide susceptibility hazard map in southwest Sweden using artificial neural network. CATENA, 183, 104225. https://doi.org/10.1016/j.catena.2019.104225

Asrizal, A., Hikmah, N., Febriya, D., & Mawaddah, F. (2023). Impact of Science Learning Materials Integrating Natural Disasters and Disaster Mitigation on Students’ Learning Outcomes: A Meta Analysis. Jurnal Penelitian Pendidikan IPA, 9(9), 586–595. https://doi.org/10.29303/jppipa.v9i9.2680

Asyari, T. D., Sailah, S., Jorena, J., & Kaban, H. (2023). Identifikasi Litologi Batuan Menggunakan Metode Geolistrik Sebagai Penyelidikan Awal Pembangunan Turap di Tepi Sungai. Jurnal Penelitian Sains, 25(3), 279. https://doi.org/10.56064/jps.v25i3.902

Ba, Q., Chen, Y., Deng, S., Wu, Q., Yang, J., & Zhang, J. (2017). An Improved Information Value Model Based on Gray Clustering for Landslide Susceptibility Mapping. ISPRS International Journal of Geo-Information, 6(1), 18. https://doi.org/10.3390/ijgi6010018

Bianchini, S., Raspini, F., Solari, L., Del Soldato, M., Ciampalini, A., Rosi, A., & Casagli, N. (2018). From Picture to Movie: Twenty Years of Ground Deformation Recording Over Tuscany Region (Italy) With Satellite InSAR. Frontiers in Earth Science, 6, 177. https://doi.org/10.3389/feart.2018.00177

Canavesi, V., Segoni, S., Rosi, A., Ting, X., Nery, T., Catani, F., & Casagli, N. (2020). Different Approaches to Use Morphometric Attributes in Landslide Susceptibility Mapping Based on Meso-Scale Spatial Units: A Case Study in Rio de Janeiro (Brazil). Remote Sensing, 12(11), 1826. https://doi.org/10.3390/rs12111826

Dharma, F., Aulia, A., Shubhan, F., & Ridwana, R. (2022). Pemanfaatan Citra Sentinel-2 Dengan Metode Ndvi Untuk Perubahan Kerapatan Vegetasi Mangrove Di Kabupaten Indramayu. Jurnal Pendidikan Geografi Undiksha. 10(2). https://doi.org/10.23887/jjpg.v10i2.42645

Diharja, R., Fahlevi, M. R., Rahayu, E. S., & Handini, W. (2022). Prototype-Design of Soil Movement Detector Using IoT Hands-on Application. Jurnal Penelitian Pendidikan IPA, 8(4), 2245–2254. https://doi.org/10.29303/jppipa.v8i4.1709

Dwinanda, I. G., Adelia, K. A. C., Wilda, R. W., Afli, F., Kaloka, T. P., & Pratiwie, D. L. (2024). Predictive Mapping of Hydrometeorological Disaster Prone Areas in Central Kalimantan. Jurnal Penelitian Pendidikan IPA, 10(2), 811–819. https://doi.org/10.29303/jppipa.v10i2.6238

Fadli, D. I., Awaliyah, I. A., Hadi, A. I., Farid, M., Akbar, A. J., & Refrizon, R. (2023). Microzonation Site Effects and Shear Strain during Earthquake Induced Landslide Using HVSR Measurement in Ulu Mana Sub-District, South Bengkulu Regency Indonesia. Jurnal Penelitian Pendidikan IPA, 9(2), 592–599. https://doi.org/10.29303/jppipa.v9i2.2961

Fathan Al-Hakim, A. F., & Rizal, Y. (2021). Fasies Sedimentasi dan Elemen Arsitektur Formasi Citalang di Desa Sidamukti, Majalengka, Provinsi Jawa Barat. Jurnal Geologi dan Sumberdaya Mineral, 22(3), 177–188. https://doi.org/10.33332/jgsm.geologi.v22i3.643

Fauza, N., Hermita, N., & Afriyani, E. (2023). Need Analysis to Develop a Physics Module Integrated Natural Disaster and Mitigation. Jurnal Penelitian Pendidikan IPA, 9(3), 1024–1029. https://doi.org/10.29303/jppipa.v9i3.3170

Febriarta, E., & Wibowo, Y. A. (2021). Kerentanan Gerakan Tanah Menggunakan Teknik Geospasial Statistik Di Macang Pacar, Nusa Tenggara Timur. Jurnal Geografi : Media Informasi Pengembangan dan Profesi Kegeografian, 18(1), 9–20. https://doi.org/10.15294/jg.v18i1.26234

Gojali, M. R., Tjahjono, B., & Rustiadi, E. (2020). Pemodelan Spasial Bahaya Longsor di Das Ciliwung Hulu, Kabupaten Bogor. Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika, 17(1), 311-318. https://doi.org/10.33751/komputasi.v17i1.1745

Haribulan, R., & Gosal, P. H. (2019). Kajian Kerentanan Fisik Bencana Longsor di Kecamatan Tomohon Utara. Jurnal Perencanaan Wilayah dan Kota, 6(3). 714-724 Retrieved from https://ejournal.unsrat.ac.id/index.php/spasial/article/view/26015

Husdi, H., & Dalai, H. (2023). Penerapan Metode Regresi Linear Untuk Prediksi Jumlah Bahan Baku Produksi Selai Bilfagi. Jurnal Informatika, 10(2), 129–135. https://doi.org/10.31294/inf.v10i2.14129

Isneni, A. N., Putranto, T. T., & Trisnawati, D. (2020). Analisis Sebaran Daerah Rawan Longsor Menggunakan Remote Sensing dan Analytical Hierarchy Process (AHP) di Kabupaten Magelang Provinsi Jawa Tengah. Jurnal Geosains dan Teknologi, 3(3), 149–160. https://doi.org/10.14710/jgt.3.3.2020.149-160

Julianto, F. D., Putri, D. P. D., & Safi’i, H. H. (2020). Analisis Perubahan Vegetasi dengan Data Sentinel-2 menggunakan Google Earth Engine (Studi Kasus Provinsi Daerah Istimewa Yogyakarta). Jurnal Penginderaan Jauh Indonesia, 2(2). 13-18. Retrieved from https://journal.its.ac.id/index.php/jpji/article/view/262

Karimah, K., Susilo, A., Suryo, E. A., Rofiq, A., & Hasan, M. F. R. (2022a). 3D Modelling of Geoelectrical Resistivity Data to Determine the Direction of Landslides in Kastoba Lake, Bawean Island, Indonesia. Jurnal Penelitian Pendidikan IPA, 8(3), 1495–1502. https://doi.org/10.29303/jppipa.v8i3.1714

Karimah, K., Susilo, A., Suryo, E. A., Rofiq, A., & Hasan, M. F. R. (2022b). Analysis of Potential Landslide Areas Using Geoelectric Methods of Resistivity in The Kastoba Lake, Bawean Island, Indonesia. Jurnal Penelitian Pendidikan IPA, 8(2), 660–665. https://doi.org/10.29303/jppipa.v8i2.1414

Lasaiba, M. A., Ansiska, P., & Tetelepta, E. G. (2024). Analisis Spasial Daya Dukung Lahan dan Pertumbuhan Permukiman Di Kecamatan Sirimau. Jurnal Tanah dan Sumberdaya Lahan, 11(2), 367–377. https://doi.org/10.21776/ub.jtsl.2024.011.2.8

Mahlianurrahman, & Aprilia, R. (2024). Development of SETS-Based Independent Curriculum Learning Module Increases Understanding of Disaster Mitigation. Jurnal Penelitian Pendidikan IPA, 10(4), 1809–1815. https://doi.org/10.29303/jppipa.v10i4.5145

Maruddani, R. F., Somantri, L., & Panjaitan, F. (2024). Analisis Spasial Perubahan Tutupan Lahan Pasca Kebakaran Hutan dan Lahan di Kabupaten Muaro Jambi. Jurnal Tanah dan Sumberdaya Lahan, 11(2), 443–453. https://doi.org/10.21776/ub.jtsl.2024.011.2.15

Nachappa, T., Ghorbanzadeh, O., Gholamnia, K., & Blaschke, T. (2020). Multi-Hazard Exposure Mapping Using Machine Learning for the State of Salzburg, Austria. Remote Sensing, 12(17), 2757. https://doi.org/10.3390/rs12172757

Nugroho, D. D., & Nugroho, H. (2020). Analisis Kerentanan Tanah Longsor Menggunakan Metode Frequency Ratio di Kabupaten Bandung Barat, Jawa Barat. Geoid, 16(1), 8. https://doi.org/10.12962/j24423998.v16i1.7680

Palloan, P., Ansar, N. A., Sulistiawaty, & Susanto, A. (2023). Analysis of Soil Physical Parameters in Landslide Prone Areas in West Battang Village, Palopo City as Early Mitigation of Landslide Disasters. Jurnal Penelitian Pendidikan IPA, 9(11), 10230–10235. https://doi.org/10.29303/jppipa.v9i11.3031

Prabandari, A. A., & Manessa, M. D. M. (2024). Analisis Perkembangan Lahan Terbangun Berdasarkan Metode Supervised Classification Menggunakan Google Earth Engine (Studi Kasus: Desa Ciputi, Kecamatan Pacet, Kab.Cianjur). Jurnal Tanah dan Sumberdaya Lahan, 11(2), 403–412. https://doi.org/10.21776/ub.jtsl.2024.011.2.11

Pratiwi, S. F., Manessa, M. D. M., & Supriatna, S. (2022). Kajian dan Evaluasi Bencana Tanah Longsor di Kecamatan Tanjungsari terhadap RTRW Kabupaten Bogor. Jurnal Wilayah dan Lingkungan, 10(1), 86–96. https://doi.org/10.14710/jwl.10.1.86-96

Purnamasari, I., Abdillah, Moc. R. W., Wijayanto, Y., Saputra, T. W., Ristiyana, S., & Budiman, S. A. (2024). Karakter Spasial dan Temporal Curah Hujan Bulanan Kabupaten Jember Berdasarkan Data Chirps. Jurnal Tanah dan Sumberdaya Lahan, 11(2), 423–432. https://doi.org/10.21776/ub.jtsl.2024.011.2.13

Rabby, Y. W., Ishtiaque, A., & Rahman, Md. S. (2020). Evaluating the Effects of Digital Elevation Models in Landslide Susceptibility Mapping in Rangamati District, Bangladesh. Remote Sensing, 12(17), 2718. https://doi.org/10.3390/rs12172718

Raharja, B. (2023). Pemetaan Litologi Menggunakan Data Citra Multispektral Perbandingan antara Citra ASTER, Landsat 8 dan Sentinel-2. Jurnal Geologi dan Sumberdaya Mineral, 24(4), 181–194. https://doi.org/10.33332/jgsm.geologi.v24i4.797

Raharjo, P. D. (2013). Penggunaan Data Penginderaan Jauh Dalam Analisis Bentukan Lahan Asal Proses Fluvial di Wilayah Karangsambung. Media Informasi Pengembangan Ilmu dan Profesi Kegeografian. 10(2).

Raharjo, P. D., & Haryono, E. (2020). Sintesa Geomorfologi Antroposen Kawasan Cagar Alam Geologi Karangsambung Bagian Selatan. Jurnal Geografi Gea, 20(2), 141–150. https://doi.org/10.17509/gea.v20i2.27727

Ramadhan, F., Riyanto, I. A., Cahyadi, A., Naufal, M., Widyastuti, M., & Adji, T. N. (2021). Dampak Siklon Tropis Savannah Terhadap Karakteristik Hidrogeokimia Aliran pada Mata Air Guntur, Kawasan Karst Gunungsewu. Jurnal Geografi : Media Informasi Pengembangan dan Profesi Kegeografian, 18(2), 90–96. https://doi.org/10.15294/jg.v18i2.30293

Rivai, W., & Hanafi, F. (2021). Pemanfaatan Wahana Unmanned Aerial Vehicle (UAV) dan GPS (Global Positioning System) untuk Analisis Tingkat Kerugian Material Penduduk pada Daerah Rawan Tanah Longsor. Jurnal Geografi : Media Informasi Pengembangan dan Profesi Kegeografian, 18(2), 97–105. https://doi.org/10.15294/jg.v18i2.30763

Safriani, E. W., Somantri, L., Rohmat, D., Setiawan, I., Panjaitan, B. R., & Arifin, A. (2024). Pemodelan Spasial Dalam Mengidentifikasi Tingkat Kerentanan Banjir Di Kecamatan Mejobo, Kabupaten Kudus, Jawa Tengah, Indonesia. Jurnal Tanah Dan Sumberdaya Lahan, 11(2), 347–357. https://doi.org/10.21776/ub.jtsl.2024.011.2.6

Setyaningsih, W., & Kurniasari, N. (2016). Pola perilaku masyarakat dalam pengurangan resiko bencana tanah longsor di kecamatan banjarwangu kabupaten banjarnegara jawa tengah. Jurnal Geografi, 13(2), 217-224. Retrieved from https://journal.unnes.ac.id/nju/JG/article/download/7978/5532

Shafique, M. (2020). Spatial and temporal evolution of co-seismic landslides after the 2005 Kashmir earthquake. Geomorphology, 362, 107228. https://doi.org/10.1016/j.geomorph.2020.107228

Sharma, L. P., Patel, N., Ghose, M. K., & Debnath, P. (2015). Development and application of Shannon’s entropy integrated information value model for landslide susceptibility assessment and zonation in Sikkim Himalayas in India. Natural Hazards, 75(2), 1555–1576. https://doi.org/10.1007/s11069-014-1378-y

Sun, D., Wen, H., Wang, D., & Xu, J. (2020). A random forest model of landslide susceptibility mapping based on hyperparameter optimization using Bayes algorithm. Geomorphology, 362, 107201. https://doi.org/10.1016/j.geomorph.2020.107201

Ulfah, S., Marzuki, M., & Susilo, A. (2021). Analysis Vulnerability Disaster of Landslide in Lantan Village Using Geoelectric Data and Sentinel Image. Jurnal Penelitian Pendidikan IPA, 7(4), 794–801. https://doi.org/10.29303/jppipa.v7i4.915

Wang, Y., Fang, Z., & Hong, H. (2019). Comparison of convolutional neural networks for landslide susceptibility mapping in Yanshan County, China. Science of The Total Environment, 666, 975–993. https://doi.org/10.1016/j.scitotenv.2019.02.263

Author Biographies

Rakhmad Fadillah, IPB University

Boedi Tjahjono, IPB University

Fifi Gus Dwiyanti, IPB University

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Copyright (c) 2024 Rakhmad Fadillah, Boedi Tjahjono, Fifi Gus Dwiyanti

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