Application of K-means clustering and B-value algorithms for analysis of earthquake-dangerous zones in Java Island
Java Island is an island with a high earthquake vulnerability. Therefore, earthquake mitigation measures are needed to reduce the impact of earthquakes. Earthquake mitigation is done by knowing the zones with a high risk of earthquakes and high levels of rock stress. The methods used to map earthquake-prone zones are K-means clustering and B-value. The K-means clustering method can provide earthquake clusters based on their characteristics and the B-value can produce rock stress conditions in the area. The results of this study are that the K-means clustering method produces 7 earthquake clusters with 5 classifications of very low, low, medium, high, and very high. In contrast, the B-value process has a high B-value with a value of 1.2-1.5 in West Java and a low B-value with a value of 0.9-1.2 in the central to the eastern part of Java.
Authors
- Y Yatini (ORCID: https://orcid.org/0000-0002-5875-9525)
- Wiji Raharjo (ORCID: https://orcid.org/0000-0002-0878-0852)
- Bentang Anggarajati
Institutions
- Universitas Pembangunan Nasional Veteran Yogyakarta (ID)
Publication Details
- Journal
- International Journal of Advances in Applied Sciences
- Published
- 2024-10-17
- DOI
- https://doi.org/10.11591/ijaas.v13.i4.pp907-915
- Primary Topic
- Data Mining and Machine Learning Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00