Skripsi

KOMPARASI KLASTERISASI DATA HISTORIS GEMPA BUMI MENGGUNAKAN DBSCAN, K-MEANS, DAN AGGLOMERATIVE CLUSTERING

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Earthquakes belong to the category of natural disasters that are prone to occur on the island of Sumatera and pose a serious challenge because they can have a devastating impact on human life, such as loss of life, material losses, and environmental damage. Consequently, earthquake hazard zone mapping is needed to provide information about the potential and history of disasters and is an important tool for disaster mitigation efforts. The objective of this study is to map earthquake vulnerability in Sumatra by comparing three clustering algorithms, namely DBSCAN, K-Means, and Agglomerative Clustering, based on earthquake data in Sumatra from 1973 to 2023. This is to find the best algorithm so that it can provide recommendations for appropriate earthquake risk mitigation strategies. The study results reveal that the K-Means algorithm is the most effective since it reached the highest Silhouette Coefficient value, namely 0.3948 with a total of 3 clusters. This research is expected to enhance the understanding of earthquake hazard zones on the island of Sumatra and provide practical contributions in the form of mitigation strategy recommendations tailored to the characteristics of each cluster to support the application of this research for the government and local communities.

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Detail Information

Series Title

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Call Number

T1894252025

Publisher

Indralaya : Prodi Sistem Informasi, Fakultas Ilmu Komputer Universitas Sriwijaya., 2025

Collation

xv, 77 hlm.; ilus.; tab.; 29 cm.

Language

Indonesia

ISBN/ISSN

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Classification

006.312 07

Content Type

Text

Media Type

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Carrier Type

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Edition

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Subject(s)

Prodi Sistem Informasi
Penambangan Data (Data Mining)

Specific Detail Info

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Statement of Responsibility

MI

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