Determination of Liquefaction-prone Zones in Lebak, Banten Using the Machine Learning Method Approach

Autor: Muhammad Rizqy Septyandy, Tito Latif Indra, Milasari Nurfitria, Urwatul Wusqa, Mediyana Listiyarini, Vina Ma'unatul Maula
Rok vydání: 2021
Předmět:
Zdroj: 2021 International Symposium on Electronics and Smart Devices (ISESD).
DOI: 10.1109/isesd53023.2021.9501604
Popis: Liquefaction is a phenomenon in which soil becomes liquefied and loses its resistance, usually caused by earthquakes. Liquefaction should be one of the considerations in planning development because this phenomenon can damage building structures. The liquefaction susceptibility was measured by the Cone Penetration Test (CPT) method. The Liquefaction Potential Index (LPI) value is obtained from the measurement results, divided into four levels (very low, low, high, very high). However, the cost required to measure only at one location point is quite expensive. In this paper, we propose a machine learning approach to modeling a liquefaction-prone zone map.
Databáze: OpenAIRE