C.45 Algorithm for Classification of Causes of Landslides

Authors

  • Yopi Handrianto AMIK BSI Bandung
  • Muhammad Farhan STMIK Nusa Mandiri

DOI:

10.33395/sinkron.v4i1.10154

Keywords:

Natural Disasters, Landslides, Decision Trees, Algorithm C4.5.

Abstract

Abstract— Natural disasters are disasters caused by natural events and cannot be avoided including earthquakes, tsunamis, volcanic eruptions, floods, hurricanes, droughts, and landslides. One of the natural disasters that often occurs in Indonesia is a landslide disaster. One of the regencies in West Java Province that had experienced a landslide was a Purwakarta district area. Landslide is one type of mass or rock mass movement, or a mixture of both, down or out of the slope due to the disruption of the stability of the soil or rocks making up the slope. With a data mining approach that uses the decision tree method or C4.5 Algorithm, a classification model will be made where the model functions as a classification of the causes of landslides in Purwakarta district.

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References

[1] Aprilla, C, D., Baskoro, D. A., Ambarwati, L., & Wicaksana, I. W. S. (2013). Data Mining dengan Rapid Miner. Jakarta: Gramedia Pustaka Utama.

[2] Fatmawati. (2016). Perbandingan Algoritma Klasifikasi Data Mining Model C4 . 5 Dan Naive Bayes Untuk Prediksi Penyakit Diabetes. Jurnal Techno Nusa Mandiri, XIII(1), 50–59.

[3] Hardiyatmo, H. C. (2012). Tanah Longsor & Erosi (Pertama; G. PRESS, Ed.). Yogyakarta: GMU PRESS.

[4] Tabrani, Muhammad (2016). Klasifikasi Penerima Beasiswa Kopertis Dengan. (1), 72–80.

[5] Nofriansyah, D. (2014). Konsep Data Mining Vs Sistem Pendukung Keputusan. Yogyakarta: deepublish.

[6] Priyono. (2015). Hubungan klasifikasi longsor, klasifikasi tanah rawan longsor dan klasifikasi tanah pertanian rawan longsor. Gema, 27(49), 1602–1617.

[7] Pusat Data Informasi dan Humas. (2017). Definisi Bencana. Retrieved June 1, 2019, from BNPB website: https://bnpb.go.id//definisi-bencana

[8] Puspita, A., & Wahyudi, M. (2015). Algoritma C4.5 Berbasis Decision Tree untuk Prediksi Kelahiran Bayi Prematur. Konferensi Nasinal Ilmu Pengetahuan Dan Teknologi (KNIT), 1(1), 97–102. Retrieved from http://konferensi.nusamandiri.ac.id/proceeding/index.php/KNIT/article/view/175

[9] Septiani, W. D. (2017). Komparasi Metode Klasifikasi Data Mining Algoritma C4.5 Dan Naive Bayes Untuk Prediksi Penyakit Hepatitis. Jurnal Pilar Nusa Mandiri, 13(1), 76–84.

[10] Sudibyo, A., Asra, T., & Rifai, B. (2018). Klasifikasi Seleksi Atribut Pada Serangan Spam. Jurnal PILAR Nusa Mandiri, 14(2), 145–150. Retrieved from http://ejournal.nusamandiri.ac.id/ejurnal/index.php/pilar/article/view/874

[11] Sukma, A. R., Halfis, R., & Hermawan, A. (2018). Klasifikasi Channel Youtube Indonesia Menggunakan Algoritma C4.5. Http://Ejournal.Bsi.Ac.Id/Ejurnal/Index.Php/Jtk, 5, 8. https://doi.org/10.31294/jtk.v4i2

[12] Supriyadi, A., Sekolah, S., Teknologi, T., Bangsa, P., & Sitasi, C. (2018). Optimasi Algoritma C4.5 Dalam Prediksi Web Phishing Menggunakan Seleksi Fitur Genetic Algoritma. Paradigma, 20(2), 27–32. https://doi.org/10.31294/p.v%vi%i.4021

[13] Undang-Undang RI. No. 24 Tahun 2007 tentang Penanggulangan Bencana. Jakarta.

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How to Cite

Handrianto, Y., & Farhan, M. (2019). C.45 Algorithm for Classification of Causes of Landslides. Sinkron : Jurnal Dan Penelitian Teknik Informatika, 4(1), 120-127. https://doi.org/10.33395/sinkron.v4i1.10154