Identifikasi Indeks Bahaya Bencana Tsunami Berbasis Sistem Informasi Geografis di Kota Palu

Shafira, Aqilla Khairani (2023) Identifikasi Indeks Bahaya Bencana Tsunami Berbasis Sistem Informasi Geografis di Kota Palu. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Wilayah Kota Palu merupakan daerah rawan bencana gempa bumi maupun tsunami karena berada di wilayah persimpangan lempeng Australia, Filipina, dan Pasifik. Pada bulan September 2018, gempa bumi dengan kekuatan 7,4 skala Richter mengguncang wilayah Sulawesi Tengah hingga memicu terjadinya bencana tsunami yang menyebabkan beberapa kerugian besar. Dalam upaya penanggulangan bencana dan mitigasi untuk mengurangi kerugian yang ditimbulkan dari bencana tsunami, dapat dilakukan pemetaan tingkat bahaya tsunami yang dikaji dari seberapa besar potensi inundasi (genangan) di daratan berdasarkan potensi ketinggian gelombang maksimum yang tiba di garis pantai. Metode yang digunakan pada penelitian ini adalah perhitungan matematis yang dikembangkan oleh Berryman dan fuzzy logic dengan menggunakan software pengolah data spasial untuk menghasilkan Peta Tingkat Bahaya Tsunami. Analisis tingkat bahaya dilakukan berdasarkan parameter kelerengan, koefisien kekasaran permukaan, ketinggian tsunami, dan garis pantai. Hasil menunjukkan bahwa Kota Palu memiliki tingkat bahaya kelas rendah, sedang, dan tinggi yang didominasi oleh kelas bahaya tinggi. Distribusi spasial tingkat bahaya bencana tsunami di Kota Palu dengan ketinggian maksimum tsunami di garis pantai sebesar 11,3 meter menyebabkan 8 kecamatan terdampak oleh sebaran genangan tsunami. Kecamatan yang memperoleh sebaran genangan terbanyak adalah Kecamatan Mantikulore dengan luas area tergenang sebesar 248,983 hektare atau memperoleh 20,309% dari total keseluruhan genangan tsunami Kota Palu. Selain itu, diperoleh luas area permukiman terdampak tsunami dengan total luas area permukiman terpapar sebesar 276,852 hektare dari total luas pemukiman sebesar 3370,862 hektare. Berdasarkan hasil peta bahaya tsunami, Kota Palu terindikasi termasuk ke dalam tingkat bahaya tsunami tinggi dengan nilai indeks bahaya tertinggi, yaitu 0,954.
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Palu City is prone to earthquakes and tsunamis because it is located at the intersection of the Australian, Philippine, and Pacific plates. In September 2018, an earthquake of 7.4 on the Richter scale shook the Central Sulawesi region, triggering a tsunami disaster that caused several significant losses. As part of disaster management and mitigation efforts to reduce the losses caused by tsunami disasters, the level of tsunami hazard can be mapped by assessing the potential inundation based on the potential maximum wave height arriving at the coastline. The methods used in this research are mathematical calculations developed by Berryman and fuzzy logic using spatial data processing software to create a Tsunami Hazard Level Map. The hazard level analysis is based on the slope parameters, surface roughness coefficient, tsunami height, and coastline. The results show that Palu City has low, medium, and high-hazard classes and is dominated by the high-hazard class. The spatial distribution of tsunami hazard levels in Palu City, with a maximum tsunami height at the coastline of 11.3 meters, caused eight districts to be affected by tsunami inundation. The district that received the most inundation was Mantikulore District, with an inundated area of 248.983 hectares or 20.309% of the total tsunami inundation in Palu City. In addition, the tsunami-affected residential area was obtained with a total exposed residential area of 276.852 hectares out of a total residential area of 3370.862 hectares. Based on the tsunami hazard map results, Palu City is categorized as having a high tsunami hazard level with the highest hazard index value of 0.954.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Indeks Bahaya, Inundasi, Kota Palu, Tsunami, Hazard Level, Inundation, Palu City, Tsunami.
Subjects:	G Geography. Anthropology. Recreation > G Geography (General) > G70.212 ArcGIS. Geographic information systems. G Geography. Anthropology. Recreation > G Geography (General) > G70.217 Geospatial data G Geography. Anthropology. Recreation > GA Mathematical geography. Cartography > GA102.4.R44 Cartography--Remote sensing H Social Sciences > HV Social pathology. Social and public welfare > HV551.5.I4 Hazard mitigation
Divisions:	Faculty of Civil, Planning, and Geo Engineering (CIVPLAN) > Geomatics Engineering > 29202-(S1) Undergraduate Thesis
Depositing User:	Aqilla Khairani Shafira
Date Deposited:	01 Aug 2023 08:44
Last Modified:	01 Aug 2023 08:44
URI:	http://repository.its.ac.id/id/eprint/100283

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