Landslides are common natural disasters in Bogor, Indonesia, triggered by a combination of factors including slope aspect, soil type and bedrock lithology, land cover and land use, and hydrologic conditions. In the Bogor area, slopes with volcanic lithologies are more susceptible to failure. GIS mapping and analysis using a Frequency Ratio Model was implemented in this study to assess the contribution of conditioning factors to landslides, and to produce a landslide susceptibility map of the study area. A landslide inventory map was prepared from a database of historic landslides events. In addition, thematic maps (soil, rainfall, land cover, and geology map) and Digital Elevation Model (DEM) were prepared to examine landslide conditioning factors. A total of 173 landslides points were mapped in the area and randomly subdivided into a training set (70%) with 116 points and test set with 57 points (30%). The relationship between landslides and conditioning factors was statistically evaluated with FR analysis. The result shows that lithology, soil, and land cover are the most important factors generating landslides. FR values were used to produce the Landslide Susceptibility Index (LSI) and the study area was divided into five zones of relative landslide susceptibility. The result of landslide susceptibility from the mid-region area of Bogor to the southern part was categorized as moderate to high landslide susceptibility zones. The results of the analysis have been validated by calculating the Area Under a Curve (AUC), which shows an accuracy of success rate of 90.10% and an accuracy of prediction rate curve of 87.30%, which indicates a high-quality susceptibility map obtained from the FR model.
ABSTRAKPeta kerentanan gerakan tanah sangat diperlukan sebagai dasar dalam perencanaan tata ruang, pemanfaatan lahan dan mitigasi bencana. Kerentanan gerakan tanah dipengaruhi oleh beberapa faktor seperti kemiringan lereng, arah lereng, litologi, tutupan lahan, elevasi, curah hujan, kelurusan, percepatan gempabumi, kurvatur, arah aliran, jarak dari sungai, dan jalan. Dalam penelitian ini dikembangkan metode pemetaan kerentanan gerakan tanah menggunakan metode kombinasi logistic regression (LR) – weight of evidence (WoE). Metode gabungan ini diharapkan dapat menghasilkan metoda yang menggabungkan kelebihan dari masing-masing metode serta sekaligus mengatasi kelemahan masing-masing metode. Wilayah studi kasus penelitian adalah Takengon, salah satu wilayah di Provinsi Aceh yang rawan terhadap bencana gempabumi dan gerakan tanah. Data yang digunakan dalam penelitian ini adalah 251 kejadian gerakan tanah secara acak yang terjadi pada tahun 2000 hingga tahun 2016. Data tersebut dibagi menjadi dua kelompok data, 70% data digunakan sebagai set data analisis untuk penyusunan model dan 30% data digunakan sebagai set data validasi untuk pengujian model. Tahapan penelitian meliputi pembobotan dua belas parameter yang mempengaruhi kerentanan gerakan tanah dengan menggunakan metode WoE. Analisis kombinasi LR-WoE menggunakan parameter hasil pembobotan metode WoE dan kemudian di analisis menggunakan statistik LR. Selanjutnya melakukan analisis perbandingan hasil pemetaan kerentanan gerakan tanah melalui pengujian kurva Receiver Operating Characteristic (ROC). Hasil validasi dan pengujian model menunjukkan bahwa metode kombinasi LR-WoE mempunyai nilai AUC 0,853 yang lebih tinggi dibandingkan menggunakan metode WoE (AUC 0,830). Berdasarkan hasil penelitian ini disimpulkan bahwa metode kombinasi LR-WoE memberikan tingkat akurasi yang lebih baik dari metode WoE untuk pemetaan kerentanan gerakan tanah. Metode kombinasi LR-WoE dapat terus dikembangkan dan dapat diusulkan menjadi metode pemetaan gerakan tanah yang akurat, efektif dan ekonomis. Kata kunci: Kerentanan gerakan tanah, Logistic Regression, Takengon, Weight of Evidence. ABSTRACTLandslide susceptibility map is an imperative basic tool for land use application, spatial planning and disaster mitigation. The susceptibility of landslide is influenced by factors such as slope, slope aspect, lithology, land cover, elevation, rainfall, linemeant, peak ground acceleration, curvature, flow direction, distance from rivers, and roads. In this research, a combined method of weight of evidence (WoE) and logistic regression (LR) was applied to assessed its advantages and overcome the limitation of each method. Takengon is an area prone to earthquake disaster and landslide. The 251 landslides from 2000 until 2016 were randomly divided into two groups of modelling/training data (70%) and validation/test data sets (30%). The research stages include weighting of twelve parameters that affect the susceptibility of landslide using the WoE method. The combination LR-WoE analysis uses the weighted parameter of the WoE method and then analyzed using LR statistics. The validation results using Receiver Operating Characteristic (ROC) curve showed that the LR-WoE method had a better accuracy than the WoE methods, with values of 0,890 higher than that of the WoE method 0,830 prediction. Therefore, it is concluded that the combined method of LR and WoE can provide a promising level of accuracy for landslide susceptibility mapping. Combined LR-WoE method can be developed and proposed to be an accurate, effective and economical method of mapping the landslides susceptibility map. Keywords: Kerentanan gerakan tanah, Logistic Regression, Takengon, Weight of Evidence.
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