Deteksi Pola Kejadian Bencana Menggunakan Algoritma Naïve Bayes di Kabupaten Boyolali
Abstract
Boyolali Regency, which is geographically located between Mount Merbabu and the still active Mount Merapi, does have high potential as a disaster-prone area. According to data from the Boyolali Regional Disaster Management Agency, during the period from 2022 to 2023, 936 disaster events were recorded in the region. These disasters have a devastating impact on ecosystems and the environment, causing significant material losses, causing psychological disorders, and even threatening human safety. In this context, detecting patterns of disaster events is an important step in disaster mitigation and management efforts. This research was conducted with the aim of understanding patterns of disaster events based on data collected by BPBD Boyolali. The method used is the Naive Bayes algorithm, which has proven to be a powerful tool in data analysis. The results of this research show a high level of accuracy of 92.52%, precision of 92.68%, and recall of 91.64% using the Naive Bayes algorithm. This indicates that the algorithm is effective in recognizing and classifying patterns of disaster events based on existing data. Thus, the results of this research can provide a valuable contribution to the development of an early disaster detection system, as well as assist the authorities in designing more effective mitigation strategies to protect the community and environment in Boyolali Regency.
References
B. Boyolali, “Badan Penanggulangan Bencana Daerah Boyolali,” 3 Oktober 2022. [Online]. Available: https://bpbd.boyolali.go.id/406-rekap-data-kejadian-bencana/688-rekap-data-kejadian-bencana-2022-sampai-juni-6127xlsx.
A. Wanto, S. Defit dan A. P. Windarto, “Algoritma Fungsi Perlatihan pada Machine Learning berbasis ANN untuk Peramalan Fenomena Bencana,” JURNAL RESTI(Rekayas a Sistem dan T eknol ogi Informasi ), vol. 5, no. 2, pp. 254-264, 2021.
A. Maulana, R. D. D. dan N. D. N. , “Implementasi Algoritma K-Means Clustering dalam Pengelompokan Data Kerusakan Rumah Akibat Bencana Alam di Kabupaten Cirebon,” JATI (Jurnal Mahasiswa Teknik Informatika), vol. 8, no. 2, 2024.
M. M. Effendi, “Analysis Prediksi Wilayah Rawan Banjir dengan Algoritma K-Means,” JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH), vol. 5, no. 2, pp. 697-703, 2024.
T. Yulianto dan F. Faisol, “Clustering Daerah Bencana Alam di Indonesia Menggunakan Metode Fuzzy C-Means,” UJMC (Unisda Journal of Mathematics and Computer science), vol. 9, no. 2, pp. 29-39, 31 Desember 2023.
M. B. Ulum dan F. Badri , “Sistem Monitoring Cuaca dan Peringatan,” JITET (Jurnal Informatika dan Teknik Elektro Terapan), vol. 11, no. 3, pp. 319-328, 2023.
Y. wahyudi, “Sistem Iot Untuk Deteksi,” dalam Seminar Nasional Teknologi dan Rekayasa, 2020.
M. Sarosa dan Nailul Muna, “Implementasi Algoritma You Only Look Once (YOLO) untuk deteksi korban bencana alam,” Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK), vol. 8, no. 4, 2021.
M. A. Islam, M. Z. S. Hadi dan R. Widyatatra, “Sistem Cerdas Pendeteksi Dan Penghitung Jumlah Korban Bencana Alam Menggunakan Algoritma Deep Learning,” JURNAL INOVTEK POLBENG, vol. 8, no. 1, 2023.
S. Triyanto, A. Sunyoto dan M. R. Arief, “Analisis Klasifikasi Bencana Banjir Berdasarkan Curah Hujan Menggunakan Algoritma Naïve Bayes,” JOISIE (Journal of Information And Informatics Engineering), vol. 5, no. 2, 2021.
D. Fitrianah, W. Gunawan dan A. P. Sari, “Studi Komparasi Algoritma Klasifikasi C5.0, SVM dan Naive Bayes dengan Studi Kasus Prediksi Banjir,” Jurnal Teknologi Informasi Techno.Com, vol. 21, no. 1, 2022.
M. F. Rifai, H. Jatnika dan B. Valentino, “Penerapan Algoritma Naïve Bayes Pada Sistem Prediksi Tingkat Kelulusan Peserta Sertifikasi Microsoft Office Specialist (MOS),” PETIR (Jurnal Pengkajian Dan Penerapan Teknik Informatika), vol. 12, no. 2, 2019.
H. Susana, “Penerapan Model Klasifikasi Metode Naive Bayes Terhadap Penggunaan Akses Internet,” JURNAL RISET SISTEM INFORMASI DAN TEKNOLOGI INFORMASI (JURSISTEKNI), vol. 4, no. 1, 2022.
N. Nurdin, M. Suhendri, Y. Afrilia dan R. Rizal, “Klasifikasi Karya Ilmiah (Tugas Akhir) Mahasiswa Menggunakan Metode Naive Bayes Classifier (NBC),” Jurnal Sistem Informasi, vol. 10, no. 2, 2021.
Murdiaty, Angela dan C. Sylvia, “Pengelompokkan Data Bencana Alam Berdasarkan Wilayah, Waktu, Jumlah Korban dan Kerusakan Fasilitas Dengan Algoritma K-Means,” JURNAL MEDIA INFORMATIKA BUDIDARMA, vol. 4, no. 3, pp. 744-752, 2020.
T. I. Hermanto dan Y. Muhyidin, “Analisis Sebaran Titik Rawan Bencana dengan K-Means Clustering dalam Penanganan Bencana,” Jurnal Sains Komputer & Informatika (J-SAKTI), vol. 5, no. 1, pp. 406-416, 2021.
D. M. Rajagukguk dan M. I. Panjaitan, “Evaluation Of Bolu Menara Sales Data With The C.45 Algorithm Using The Rapid Miner Application,” Journal Of Data Science, vol. 1, no. 2, 2023.
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