Analisis Risiko Tanah Longsor Akibat Curah Hujan Di Daerah Pujon Malang Menggunakan Non Stationary Extreme Value

Salsabilla, Febbianti Mifta (2023) Analisis Risiko Tanah Longsor Akibat Curah Hujan Di Daerah Pujon Malang Menggunakan Non Stationary Extreme Value. Other thesis, Institut Teknologi Sepuluh Nopember Surabaya.

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Abstract

Salah satu bencana yang sering terjadi di Indonesia adalah bencana tanah longsor. Salah satu faktor penyebab tanah longsor yaitu terjadinya hujan lebat, sehingga tanah akan bertambah massanya, dan terjadilah tanah longsor. Sebagai bentuk upaya mitigasi untuk mengurangi kerugian seperti korban jiwa, aset, dan lainnya, perlu dilakukan analisis risiko untuk mitigasi bencana tanah longsor. Risiko tanah longsor merupakan suatu perhitungan penggabungan antara probabilitas temporal dan probabilitas spasial. Pada probabilitas temporal pada penelitian kali ini digunakan dengan melihat data historis curah hujan yang seringkali pada penelitian lain digunakan asumsi stasioner, padahal dengan perubahan iklim menyebabkan terjadinya perubahan curah hujan hujan berdasarkan waktu, sehingga penelitian ini menggunakan metode Non-Stasionary Extreme Value. Metode Non-Stasionary Extreme Value yang digunakan didasarkan pada distribusi Generalized Extreme Value (GEV), dimana sebelumnya tetap dilakukan pengujian apakah terdapat pola atau tren pada data menggunakan Mann Kendall Trend Test. Kemudian pada probabilitas spasial digunakan data kerentanan daerah berupa shapefile yang dianalisis menggunakan analisis spasial, yaitu menggunakan metode esktraksi, dan statistik pada spasial. Objek pada penelitian kali ini berada di Pujon Malang yang dikenal dengan daerah wisata rawan longsor. Hasil dari penelitian ini didapatkan probabilitas tanah longsor dengan semakin tinggi nilai periode tahun yang akan mendatang, akan semakin besar probabilitas akan terjadinya tanah longsor, dan probabilitas tanah longsor yang paling besar terdapat pada kelas kerentanan sedang
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One of the disasters that often occurs in Indonesia is landslides. One of the factors that cause landslides is of heavy rain, so that the soil will increase in mass, and landslides occur. As a form of mitigation efforts to reduce losses such as loss of life, assets, and others, it is necessary to carry out a risk analysis for landslide disaster mitigation. Landslide risk is a combined calculation between temporal probability and spatial probability. The temporal probability used in this study is historical rainfall data. Usually rainfall data is assumed as stationary event, but in reality whereas climate change causes changes in rainfall based on time. So in this study, Non-Stationary Extreme Value method is used. Non-Stationary Extreme Value method that used is based on the Generalized Extreme Value (GEV) distribution, where previously it was still tested whether there was a pattern or trend in the data using the Mann Kendall Trend Test. Then for calculating spatial probability, regional vulnerability data is used in the form of shapefiles which is analyzed using spatial analysis, namely extraction method and spatial statistics. This research is analyzed for Pujon Malang region, which is known as a landslide-prone tourist area. The results obtain the probability of landslides with the higher the value of the next year's period, the greater the probability that landslides will occur, and the greatest probability of landslides is in the medium vulnerability class

Item Type:	Thesis (Other)
Uncontrolled Keywords:	curah hujan, kerentanan, non stationary extreme value, risiko, tanah longsor
Subjects:	G Geography. Anthropology. Recreation > GA Mathematical geography. Cartography > GA139 Digital Elevation Model (computer program) Q Science > Q Science (General) > Q180.55.M38 Mathematical models Q Science > QA Mathematics > QA401 Mathematical models.
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Actuaria > 94203-(S1) Undergraduate Thesis
Depositing User:	Febbianti Mifta Salsabilla
Date Deposited:	20 Jan 2023 06:38
Last Modified:	20 Jan 2023 06:38
URI:	http://repository.its.ac.id/id/eprint/95534

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