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Prediction and Visualization of Flood Occurences in Tangerang using K-Medoids, DBScan, and X-Means Clustering Algorithms

Natalia, Friska and Desanti, Ririn Ikana and Ferdinand, Ferry Vincenttius (2020) Prediction and Visualization of Flood Occurences in Tangerang using K-Medoids, DBScan, and X-Means Clustering Algorithms. In: 5th International Conference on New Media Studies, 9-11 Oct. 2019, Bali, Indonesia.

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Official URL: https://ieeexplore.ieee.org/document/8981859/metri...

Abstract

The object of this research is the Tangerang area due to losses and damage due to floods in Tangerang in 2016, many people suffered due to flooding also many people were displaced. In the Tangerang area, there are no applications that can detect potential flooding and the geographical location of Tangerang is close to the Jakarta and Bogor areas. This research purpose will focus on observation, identification of research objects, collecting data, and conducting surveys. The visualization mapping of flood prediction in Tangerang City to display visualization information on river water levels in the Tangerang area by clustering using Power BI. This research objectives knowing the prediction of river water levels in the Tangerang area, including the Cisadane River, Angke River, and Pesanggrahan River using three clustering algorithms (K-Medoids, DBScan, X-Means).

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Visualisation , Prediction , K-Medoids , DBScan , X-Means
Subjects: 000 Computer Science, Information and General Works > 000 Computer Science, Knowledge and Systems > 006 Special Computer Methods (Artificial Intelligence, Machine Learning, 3D Graphics, Digital Video, Data Mining, Augmented Reality)
500 Science and Mathematic > 510 Mathematics > 519 Probabilities and Applied Mathematics
Q Science > QA Mathematics > QA273-280 Probabilities. Mathematical statistics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Fakultas Teknik Informatika > Program Studi Sistem Informasi
Depositing User: mr admin umn
Date Deposited: 24 Nov 2021 15:56
Last Modified: 24 Nov 2021 15:56
URI: http://kc.umn.ac.id/id/eprint/19269

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