ANALISA PREDIKSI EFEK KERUSAKAN GEMPA DARI MAGNITUDO (SKALA RICHTER) DENGAN METODE ALGORITMA ID3 MENGGUNAKAN APLIKASI DATA MINING ORANGE
DOI:
https://doi.org/10.47111/jti.v14i2.1079Keywords:
Klasifikasi, ID3, Data mining, Naives Baiyes, Gempa bumiAbstract
Earthquakes are relatively common natural disasters in Indonesia, mainly due to the interaction of tectonic plates. In this study the seismic energy recorded on the seismograph was measured on the Richter Scale (SR). The dataset collected during Semester 1 of 2019 from the Meteorology and Geophysics, Climatology Agency (BMKG) noted that there were many seismic energy vibrations occurring from small to large around Indonesia. Furthermore, for the attributes of the dataset that have been collected include Date / Time, Longitude, Latitude, Depth (Km), Magnitude (SR), Range of depth (Km) and the effect of earthquake damage selected as the class of the dataset collected, in this study the authors used the method classification with ID3 algorithm to produce effective prediction data for the benefit of earthquake early warning in the Indonesian archipelago.
Downloads
References
Data Online Pusat Database BMKG. (Online), (http://dataonline.bmkg.go.id/home).
Pribadi, Khrisna S, dkk. 2008. Buku Pegangan Guru Pendidikan Siaga Bencana. Bandung : Pusat Mitigasi Bencana ITB.
R prathivi, optimasi algoritme naive bayes untuk klasifikasi data gempa bumi di indonesia berdasarkan hiposentrum , purwokerto : amikom, 2020.
BNPB.2014.Data & informasi Bencana Indonesia. (Online) (http://dibi.bnpb.go.id/DesInventar/data_profil_wilayah.jsp) .
Mohammad Ihsan, Analisa Ketahanan Gempa. Bab. 2, FT UI, 2008.
Kholisul Fatikhin, Data Mining-Pendahuluan. Bab 1, FT UI, 2010.
Mochammad Haldi Widianto, Algoritma Naives Baiyes, Binus University, 2019.
Intan Noviantari Manyoe, Lantu Lantu, Samsu Arif, Rakhmat Jaya Lahay, Earthquake Damage Level of Gorontalo Area Based on Seismicity and Peak Ground Acceleration, Jambura Geoscience Review, 2019.
Dito Putro Utomo, Bister Purba. Penerapan Datamining pada Data Gempa Bumi Terhadap Potensi Tsunami di Indonesia. Prosiding Seminar Nasional Riset Information Science (SENARIS), 2019.
C. Fatichah, D. Purwitasari, Deteksi Gempa Berdasarkan Data Twitter Menggunakan Decision ID3, Random Forest, dan SVM. Jurnal Teknik ITS, 2017.
E. Buulolo, N. Silalahi, Fadlina and R. Rahim, C4.5 Algorithm To Predict the Impact of the, International Journal of Engineering Research & Technology (IJERT), vol. 6, no. 2, pp.10-15, 2017.
S. F. Rodiyansyah and E. Winarko, Klasifikasi Posting Twitter Kemacetan Lalu Lintas Kota Bandung Menggunakan NaiveBayesian Classification, Indonesian Journal of Computing and Cybernetics System (IJCCS), vol. 6, no. 1, pp. 91-100, 2012.
A. Jananto, Algoritma Naive Bayes untuk Mencari Perkiraan Waktu Studi Mahasiswa, Jurnal Teknologi Informasi DINAMIK , vol. 18, no. 1, pp. 09-16, 2013.
Sunarjo, M. T. Gunawan and S. Pribadi, Gempa Bumi Edisi Populer, Jakarta: Badan Meteorologi, Klimatologi dan Geofsika, 2012.
Rendra Dwi Lingga P., Chastine Fatichah, Diana Purwitasari, Deteksi Gempa Berdasarkan Data Twitter Menggunakan Decision ID3, Random Forest, dan SVM, Jurnal Teknik ITS, 2017.
S. F. Rodiyansyah and E. Winarko, Klasifikasi Posting Twitter Kemacetan Lalu Lintas Kota Bandung Menggunakan NaiveBayesian Classification, Indonesian Journal of Computing and Cybernetics System (IJCCS), vol. 6, no. 1, pp. 91-100, 2012.