Sistem Informasi Geografis Risiko Kemunculan Rip Current Menggunakan Decision Tree C4.5

Made Leo Radhitya(1), Agus Harjoko(2*)

(2) Departemen Ilmu Komputer dan Elektronika, FMIPA UGM, Yogyakarta
(*) Corresponding Author


One of the dangers that occur at the beach is rip current. Rip current poses significant danger for beachgoers. This paper proposes a method to predict the rip current's occurence risk by using decision tree generated using C4.5 algorithm. The output from the decision tree is rip current's occurrence risk. The case study for this research is the beach located at Rote Island, Rote Ndao, Nusa Tenggara Timur. Evaluation result shows that the accuracy is 0.84, and the precision is 0.61. The average recall value is 0.68 and the average F-measure is 0.59 in the range 0 to 1.


GIS, Rip current, Decision tree, C4.5

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