WAHYU, AAN (2022) KLASTERISASI DAMPAK BENCANA GEMPA BUMI MENGGUNAKAN ALGORITMA K-MEANS DI PULAU JAWA. S1 thesis, Universitas Mercu Buana Jakarta-Menteng.
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Abstract
Dari semua bencana alam yang terjadi, gempa bumi adalah yang paling sering terjadi di Indonesia. Kajian seismogenetik menunjukkan pulau Jawa merupakan salah satu daerah rawan gempa bumi. Seperti diketahui bahwa pulau jawa memiliki populasi penduduk yang padat. Dikarenakan alasan tersebut, pemerintah diharuskan untuk memberikan perhatian lebih pada penanggulangan bencana khususnya gempa bumi. Dengan tujuan mengurangi jumlah korban jiwa. Maka dari itu dibutuhkan sebuah algoritma untuk melakukan klasterisasi data dampak gempa bumi dengan tujuan untuk membantu pihak - pihak bersangkutan dalam mengambil keputusan. Penelitian ini melakukan klasterisasi data pesebaran dampak bencana gempa bumi (2012 - 2021) dari Badan Nasional Penanggunlangan Bencana (BNPB) menggunakan algoritma K-Means Clustering. Dari penelitian ini ditemukan bahwa dampak bencana dapat dibagi menjadi 4 klaster. Klaster 1 memiliki dampak bencana paling banyak meliputi meninggal, luka, menderita, mengungsi, kerusakan rumah, fasilitas pendidikan, fasilitas kesehatan, fasilitas ibadah, kantor, jembatan, dan kios. Klaster ini memiliki Mean Absolute Error (MAE) senilai 0,017, Mean Square Error (MSE) senilai 0,002, standar deviasi senilai 0,255 dan variance senilai 0,065. Klaster 2 memiliki dampak bencana paling banyak kedua meliputi meninggal, luka, menderita, mengungsi, rumah, fasilitas pendidikan, fasilitas kesehatan, fasilitas ibadah, pada korban menderita, mengungsi, kerusakan rumah dan fasilitas ibadah. Klaster ini memperoleh MAE senilai 0,053, MSE senilai 0,011, standar deviasi senilai 0,249 dan variance senilai 0,062. Klaster 3 memiliki dampak bencana paling banyak ketiga meliputi korban luka, menderita, mengungsi, kerusakan rumah, fasilitas pendidikan, fasilitas kesehatan, fasilitas ibadah dan kantor. klaster ini memperoleh MAE senilai 0,102, MSE senilai 0,039, standar deviasi senilai 0,212 dan variance senilai 0,045. Klaster 0 memiliki dampak bencana paling sedikit meliputi kerusakan rumah, fasilitas pendidikan, fasilitas kesehatan, fasilitas ibadah, kantor, dan kios. klaster ini memperoleh MAE sebesar 0,021, MSE senilai 0,005, standar deviasi senilai 0,251 dan variance senilai 0,063. Of all the natural disasters that occur, earthquakes are the most frequent in Indonesia. Seismogenetic studies show that the island of Java is one of the earthquake-prone areas. As is known that the island of Java has a dense population. Due to this reason, the government is required to pay more attention to disaster management, especially earthquakes. With the aim of reducing the number of fatalities. Therefore, an algorithm is needed to cluster earthquake impact data with the aim of helping the parties concerned in making decisions. This study clustered data on the distribution of the impact of the earthquake disaster (2012 - 2021) from the National Disaster Management Agency (BNPB) using the K-Means Clustering algorithm. From this study it was found that the impact of disasters can be divided into 4 clusters. Cluster 1 has the most disaster impacts including death, injury, suffering, displacement, damage to houses, educational facilities, health facilities, worship facilities, offices, bridges, and kiosks. This cluster has a Mean Absolute Error (MAE) of 0.017, a Mean Square Error (MSE of 0.002, a standard deviation of 0.255 and a variance of 0.065. Cluster 2 has the second largest disaster impact including death, injury, suffering, evacuation, houses, educational facilities, health facilities, worship facilities, for victims suffering, evacuating, damage to houses and worship facilities. This cluster obtained an MAE of 0.053, an MSE of 0.011, a standard deviation of 0.249 and a variance of 0.062. Cluster 3 has the third most disaster impact including injured, suffering, displaced, damage to houses, educational facilities, health facilities, worship facilities and offices. This cluster obtained MAE of 0.102, MSE of 0.039, standard deviation of 0.212 and variance of 0.045. Cluster 0 has the least disaster impact including damage to houses, educational facilities, health facilities, worship facilities, offices, and kiosks. This cluster obtained an MAE of 0.021, an MSE of 0.005, a standard deviation of 0.251 and a variance of 0.063.
| Item Type: | Thesis (S1) |
|---|---|
| NIM/NIDN Creators: | 41517120054 |
| Uncontrolled Keywords: | Disaster, Clustering, Impact, K-Means,Bencana, Clustering, Dampak |
| Subjects: | 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika |
| Divisions: | Fakultas Ilmu Komputer > Informatika |
| Depositing User: | Priyo Raharjo |
| Date Deposited: | 09 Sep 2022 03:40 |
| Last Modified: | 09 Sep 2022 03:40 |
| URI: | http://repository.mercubuana.ac.id/id/eprint/68890 |
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