Model Inhomogeneous Neyman-Scott Cox Process Untuk Pemetaan Risiko Gempabumi Di Pulau Sumatera

Metrikasari, Rahma (2020) Model Inhomogeneous Neyman-Scott Cox Process Untuk Pemetaan Risiko Gempabumi Di Pulau Sumatera. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Kondisi geografis Indonesia yang berada pada jalur sirkum pasifik dan terletak diantara pertemuan tiga lempeng tektonik menjadikan Indonesia sebagai salah satu negara dengan tingkat risiko gempa yang tinggi. Salah satu wilayah rawan gempa di Indonesia adalah pulau Sumatera. Pada penelitian ini, kejadian gempa di pulau Sumatera dimodelkan dengan inhomogeneous Neyman-Scott Cox Process karena proses terjadinya gempabumi secara umum diawali dengan gempa utama dan diikuti oleh gempa susulan, sehingga persebaran titik gempa di pulau Sumatera cenderung mengelompok di wilayah tertentu. Selain itu, terdapat kecenderungan bahwa gempabumi terjadi di daerah yang dekat dengan gunung berapi, zona subduksi, dan sesar aktif. Hasil eksplorasi data menunjukkan bahwa data gempabumi di pulau Sumatera tidak homogen yang dimungkinkan karena faktor geologis di pulau Sumatera seperti keberadaan gunung berapi, zona subduksi, dan sesar aktif. Selain itu, analisis korelasi spasial menunjukkan bahwa pola persebaran gempabumi di Sumatera cenderung membentuk cluster. Pemodelan kejadian gempa dengan inhomogeneous Neyman-Scott Cox Process menunjukkan faktor jarak subduksi dan sesar secara signifikan mempengaruhi risiko terjadinya gempa. Jika jarak suatu lokasi mendekat sejauh 100 km ke zona subduksi, maka risiko terjadinya gempa di sekitar lokasi tersebut meningkat sebesar 1.9 kali sedangkan jika jarak suatu lokasi ke sesar mendekat sejauh 100 km, maka risiko terjadinya gempa di sekitar lokasi tersebut meningkat sebesar 1.7 kali. Validasi model dengan plot envelope K-function menunjukkan bahwa inhomogeneous Neyman-Scott Cox Process baik digunakan untuk memodelkan data gempa di pulau Sumatera selama periode 2009-2018 dengan magnitudo ≥ 4.
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The geographical condition of Indonesia, which is on the Pacific Circum lane and located between three tectonic plates, makes Indonesia one of the countries with a high level of earthquake risk. One of the earthquake prone areas in Indonesia is the island of Sumatra. In this study, the earthquake event on the island of Sumatra was modeled with inhomogeneous Neyman-Scott Cox Process because the process of earthquake occurrence was generally preceded by a major earthquake and followed by aftershocks, so the distribution of earthquake points on the island of Sumatra tends to cluster in certain areas. In addition, there is a tendency that earthquakes occur in areas close to volcanoes, subduction zones, and active faults. The results of data exploration indicate that earthquake data on the island of Sumatra is not homogeneous which is possible due to geological factors on the island of Sumatra such as the presence of volcanoes, subduction zones, and active faults. In addition, spatial correlation analysis shows that the pattern of earthquake distribution in Sumatera tends to form clusters. Modeling earthquake events with inhomogeneous Neyman-Scott Cox Process shows the subduction distance and fault factors significantly influence the risk of earthquake occurrence. If the distance of a location approaches 100 km to the subduction zone, the risk of an earthquake around that location increases by 1.9 times whereas if the distance of a location to the fault approaches 100 km, the risk of an earthquake around that location increases by 1.7 times. Model validation with K-function envelope plot shows that inhomogeneous Neyman-Scott Cox Process is good to be used to model earthquake data on the island of Sumatra during the period 2009-2018 with a magnitude of ≥ 4.

Item Type: Thesis (Other)
Additional Information: RSSt 519.53 Met m-1 • Metrikasari, Rahma
Uncontrolled Keywords: Cluster, Cox Process, Fault, Subduction, Volcano,Cluster, Cox Process, Gunung Berapi, Sesar, Subduksi.
Subjects: Q Science > QA Mathematics > QA278.55 Cluster analysis
Divisions: Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49201-(S1) Undergraduate Thesis
Depositing User: Metrikasari Rahma
Date Deposited: 25 Aug 2020 05:36
Last Modified: 23 Nov 2023 01:04
URI: http://repository.its.ac.id/id/eprint/81113

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