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All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi International Journal of Hydrological and Environmental for Sustainability
Naqiya, Sadiyana Yaqutna
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Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Earth & Planetary Sciences Environmental Science Mathematics

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Bayesian Spatial Modeling of Landslide Events Using Integrated Nested Laplace Approximation (INLA): A Study Case on Natural Conditions and Community Actions in East Java, Indonesia Alfarisi, Salman; Christina, Athalia; Naqiya, Sadiyana Yaqutna; Rachmawati, Ro'fah Nur; Machmud, Amir; Palupi, Endah Kinarya
International Journal of Hydrological and Environmental for Sustainability Vol. 2 No. 3 (2023): International Journal of Hydrological and Environmental for Sustainability
Publisher : CV FOUNDAE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/ijhes.v2i3.354

Abstract

Bayesian Spatial Modeling Using Integrated Nested Laplace Approximation (INLA) is an advanced statistical technique that can be used to model and analyze occurrences in geographic areas. Landslides are one of natural disasters that occur due to natural and human factors and pose a serious threat to East Java Province which has complex natural conditions. The disaster brings various losses, including economic, infrastructural, human life, and environmental. This study investigates the factors contributing to landslides across 29 districts and 9 cities in East Java, Indonesia, using spatial regression modeling by Integrated Nested Laplace Approximation (INLA). The factors include the number of seaside villages, the number of slope topography villages, and the area of temporarily uncultivated gardens and fields in 2021. The modeling results show that the number of seaside villages, the number of slope topography villages, and the area of fields that are temporarily uncultivated have a significant influence on the occurrence of landslides so that efforts to mitigate and prevent such disasters can be focused on the contributing factors. We conclude that the model might be able to identify potential landslide risk areas through mapping.
Development of a Fuzzy Logic Model for Tsunami Early Detection Using Tunami F1 on the Southern Coast of Yogyakarta International Airport, Jogja Naqiya, Sadiyana Yaqutna; Khoirunnisa, Hanah; Pradananta, Galih
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 2 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v10i2.35416

Abstract

Tsunami disaster mitigation requires a reliable early warning system to reduce traumatic impacts and material losses. This study develops a fuzzy logic model for early tsunami detection by integrating wave height (SSH) and estimated tsunami arrival time (ETATSU) parameters. The model is combined with the TUNAMI F1 simulation, which considers seabed topography and fluid dynamics. Simulations were conducted on 36 earthquake scenarios on the southern coast near Yogyakarta International Airport (YIA). The results show that the model successfully classifies tsunami risks into three categories: alert, standby, and emergency, with an overall accuracy of 83.3%. Some scenarios showed invalid results at high magnitudes (Mw ≥ 8.5). This research improves the accuracy of tsunami early warning systems, potentially saving more lives and minimizing the impact of disasters.
Co-Authors Amir Machmud, Amir Christina, Athalia Hanah Khoirunnisa, Hanah Palupi, Endah Kinarya Pradananta, Galih Rachmawati, Ro'fah Nur Salman Alfarisi