Paper The following article is Open access

Classification tide levels in Semarang City use support vector machine

, , , and

Published under licence by IOP Publishing Ltd
, , Citation Sugito et al 2019 J. Phys.: Conf. Ser. 1217 012103 DOI 10.1088/1742-6596/1217/1/012103

1742-6596/1217/1/012103

Abstract

As the capital of Central Java, Semarang is a coastal town located on the north coast of Java. This geographical feature exposes the city to environmental problems such as tidal flood (locally known as rob). Therefore, it is high at stake for the city to classify a certain model to determine the high of tide. One of the expert classification methods of machine-based learning is support vector machine (SVM), it is classified as the nonparametric machine which does not require any assumptions. The classification using SVM requires a kernel as a weight to determine support vector data to classify. Therefore, this study uses Kernel of polynomial and radial base function. As for variables of tidal classification, this study used wind speed and rainfall. On the basis of the analysis, the maximum tide level classification accuracy was carried out on the distribution of 80: 20 training and testing data resulting in a classification accuracy of 69.42%. Classification accuracy was determined by the distribution of training and testing data.

Export citation and abstract BibTeX RIS

Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

Please wait… references are loading.
10.1088/1742-6596/1217/1/012103