Pemetaan Risiko Longsor Berbasis Slope, Aspect, dan Curvature pada Agroindustri Tahu (Studi Kasus di Desa Sambak, Magelang)

Authors

  • Anak Agung Caresasha Adinda Dea Program Studi Teknik Pertanian, Fakultas Teknologi Pertanian, Universitas Udayana
  • Ni Nyoman Sulastri Program Studi Teknik Pertanian, Fakultas Teknologi Pertanian, Universitas Udayana
  • Ngadisih Ngadisih 2 Departemen Teknik Pertanian dan Biosistem, Fakultas Teknologi Pertanian, Universitas Gadjah Mada, Sleman, Daerah Istimewa Yogyakarta, Indonesia
  • Ida Bagus Ary Purnayama Parbawa Program Studi Teknik Pertanian dan Biosistem, Fakultas Teknologi Pertanian, Universitas Udayana, Badung, Bali, Indonesia
  • Komang Ratih Indah Pradnyani Program Studi Teknik Pertanian dan Biosistem, Fakultas Teknologi Pertanian, Universitas Udayana, Badung, Bali, Indonesia .

Keywords:

agroindustri tahu, analisis resiko, frequency ratio, longsor, QGIS

Abstract

Tanah longsor merupakan salah satu bencana geologi yang berpotensi menimbulkan dampak signifikan terhadap keberlanjutan kegiatan sosial dan ekonomi masyarakat, khususnya pada wilayah perbukitan. Desa Sambak, Kecamatan Kajoran, Kabupaten Magelang, merupakan kawasan dengan kondisi topografi curam yang berkembang sebagai sentra agroindustri tahu, sehingga memiliki tingkat risiko longsor yang perlu dikaji secara sistematis. Penelitian ini bertujuan untuk menganalisis dan memetakan risiko longsor sebagai dasar perencanaan mitigasi yang berkelanjutan bagi keberlangsungan agroindustri tahu di wilayah tersebut. Analisis dilakukan menggunakan data digital surface model (DSM) resolusi 0,45 m yang diolah untuk menghasilkan parameter kemiringan lereng (slope), arah hadap lereng (aspect), dan kelengkungan lereng (curvature). Metode frequency ratio (FR) digunakan untuk menentukan tingkat kerawanan dan bahaya longsor berdasarkan hubungan antara parameter topografi dan kejadian longsor, sedangkan variabel kerentanan (vulnerability) dan kapasitas (capacity) dianalisis menggunakan interpolasi inverse distance weighted (IDW). Seluruh pengolahan data spasial dilakukan dengan perangkat lunak QGIS 3.18. Hasil analisis menunjukkan bahwa wilayah penelitian terbagi ke dalam tiga kelas risiko longsor, yaitu risiko rendah, sedang, dan tinggi. Sebagian besar lokasi agroindustri tahu berada pada kelas risiko sedang, sementara dua lokasi teridentifikasi berada pada kelas risiko tinggi. Kondisi ini mengindikasikan perlunya upaya mitigasi yang terarah guna menjaga keberlanjutan usaha agroindustri serta mengurangi potensi kerugian akibat bencana longsor.

References

BNPB. (2023). Buku data bencana Indonesia 2023. Buku Data Bencana Indonesia, 3, 3–11.

BNPB. (2024). Indeks risiko bencana Indonesia tahun 2024. In Badan Nasional Penanggulangan Bencana (Vol. 03).

Çellek, S. (2022). Effect of the slope angle and its classification on landslides. Himalayan Geology, 43(1), 85–95.

Erzagian, E., Wilopo, W., & Fathani, T. F. (2023). Landslide susceptibility zonation using GIS-based frequency ratio approach in the Kulon Progo mountains area, Indonesia. Progress in Landslide Research and Technology, Part F4147(2), 115–126. https://doi.org/10.1007/978-3-031-44296-4_3

Ma, W., Dong, J., Wei, Z., Peng, L., Wu, Q., Wang, X., Dong, Y., & Wu, Y. (2023). Landslide susceptibility assessment using the certainty factor and deep neural network. Frontiers in Earth Science, 10(January), 1–14. https://doi.org/10.3389/feart.2022.1091560

Naseer, S., Haq, T. U., Khan, A., Tanoli, J. I., Khan, N. G., Qaiser, F. ur R., & Shah, S. T. H. (2021). GIS-based spatial landslide distribution analysis of district Neelum, AJK, Pakistan. Natural Hazards, 106(1), 965–989. https://doi.org/10.1007/s11069-021-04502-5

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

Pradhan, B. (2010). Landslide susceptibility mapping of a catchment area using frequency ratio, fuzzy logic and multivariate logistic regression approaches. Journal of the Indian Society of Remote Sensing, 38(2), 301–320. https://doi.org/10.1007/s12524-010-0020-z

Putra, M. S. G. P., Anggraini, N., & Wahyuni, D. (2025). Landslide mitigation strategies in riverbank areas: A step-by-step guide to design retaining wall (Vol. 1). Atlantis Press International BV. https://doi.org/10.2991/978-94-6463-678-9_14

Rakuasa, H.-, Somae, G., Sihasale, D. A., Pakniany, Y., Septory, J. S. I., & Latue, P. C. (2023). Analisis spasial daerah rawan longsor di Kecamatan Damer, Kabupaten Maluku Barat Daya, Provinsi Maluku. El-Jughrafiyah, 3(1), 62. https://doi.org/10.24014/jej.v3i1.20278

Saha, A. K., Gupta, R. P., & Arora, M. K. (2002). GIS-based landslide hazard zonation in the Bhagirathi (Ganga) Valley, Himalayas. International Journal of Remote Sensing, 23(2), 357–369. https://doi.org/10.1080/01431160010014260

Sheng, M., Zhou, J., Chen, X., Teng, Y., Hong, A., & Liu, G. (2022). Landslide susceptibility prediction based on frequency ratio method and C5.0 decision tree model. Frontiers in Earth Science, 10(May), 1–14. https://doi.org/10.3389/feart.2022.918386

Silalahi, F. E. S., Pamela, Arifianti, Y., & Hidayat, F. (2019). Landslide susceptibility assessment using frequency ratio model in Bogor, West Java, Indonesia. Geoscience Letters, 6(1). https://doi.org/10.1186/s40562-019-0140-4

Somae, G., Supriatna, S., Manessa, M. D. M., & Rakuasa, H. (2022). SMORPH application for analysis of landslide prone areas in Sisimau District, Ambon City. Social, Humanities, and Educational Studies (SHES): Conference Series, 5(4), 11. https://doi.org/10.20961/shes.v5i4.68936

UNDRR. (2004). Risk awareness and assessment. Living with Risk: A Global Review of Disaster Reduction Initiatives, 36–78.

Wang, Z., Goetz, J., & Brenning, A. (2022). Transfer learning for landslide susceptibility modeling using domain adaptation and case-based reasoning. Geoscientific Model Development, 15(23), 8765–8784. https://doi.org/10.5194/gmd-15-8765-2022

Wibawanti, E., Sartohadi, J., Ngadisih, N., Setiawan, A., & Mardiatno, D. (2023). Keefektifan “ProKlim” dalam pengendalian longsor secara vegetatif di Kampung Iklim Desa Sambak, Kajoran, Magelang. AgriTECH, 43(2), 105. https://doi.org/10.22146/agritech.72009

Zhang, Q. (2024). Spatial distribution prediction of landslide susceptibility based on integrated particle swarm optimization. Frontiers in Earth Science, 12(December). https://doi.org/10.3389/feart.2024.1516615

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Published

2026-05-18

How to Cite

Dea, A. A. C. A., Sulastri, N. N., Ngadisih, N., Ary Purnayama Parbawa, I. B., & Ratih Indah Pradnyani, K. (2026). Pemetaan Risiko Longsor Berbasis Slope, Aspect, dan Curvature pada Agroindustri Tahu (Studi Kasus di Desa Sambak, Magelang). Jurnal BETA (Biosistem Dan Teknik Pertanian), 14(2). Retrieved from https://ejournal3.unud.ac.id/index.php/beta/article/view/2044

Issue

Vol. 14 No. 2 (2026): INPRESS

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Copyright (c) 2026 Anak Agung Caresasha Adinda Dea, Ni Nyoman Sulastri, Ngadisih Ngadisih, Ida Bagus Ary Purnayama Parbawa, Komang Ratih Indah Pradnyani

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