ANDROID BASED DISASTER LOCATION INFORMATION APPLICATION
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Abstract
Android Based Disaster Location Information Application Designer. This research was motivated by the length of time officers took to handle a disaster and the officers did not yet know the real location when the disaster occurred. In designing disaster location information applications, there are several menus that can support the speed of officers in handling disasters. In this application there is also a graphic feature of disaster risk levels in the Kediri City area. This risk level determination is taken in the cluster identification process using 3 levels of disaster prone grouping, namely low, medium and high. This grouping level is taken based on the level of grouping of disaster-prone areas of the Kediri City BPBD.
The results of grouping through the cluster identification process show that in the Flood Disaster Event the risk level in Mojoroto sub-district is at the High level with a percentage of 66.7% and Kota Sub-district is at the Medium level with a percentage of 16.7% and Islamic boarding school sub-district is at the Low level with a percentage of 16.7 %. In the event of a landslide disaster, the risk level in the Mojoroto sub-district is at the High level with a percentage of 50% and the Kota sub-district is at the Medium level with a percentage of 25% and the Islamic boarding school sub-district is at the Low level with a percentage of 25%. In the event of a drought disaster, the risk level in Mojoroto sub-district is at the Medium level with a percentage of 33.3%, and Kota Sub-district is at the Medium level with a percentage of 33.3% and Islamic boarding school sub-district is at the Medium level with a percentage of 33.3%. In the event of an Extreme Weather Disaster, the risk level in Mojoroto sub-district is at the High level with a percentage of 43.6% and Kota Sub-district is at the Medium level with a percentage of 30.9% and Islamic boarding school sub-district is at the Low level with a percentage of 25.5%. In the event of an Earthquake Disaster, the risk level in Mojoroto sub-district is at the Medium level with a percentage of 33.3%, and Kota Sub-district is at the Medium level with a percentage of 33.3% and Islamic boarding school sub-district is at the Medium level with a percentage of 33.3%. In the event of the Covid-19 Disaster, the risk level in Mojoroto sub-district is at Low level with a percentage of 29.8%, and Kota Sub-district is at Medium level with a percentage of 33.5% and Islamic boarding school sub-district is at High level with a percentage of 36.8%. The results of this grouping will make it easier for officers to select and sort out which areas are prioritized for alerting personnel to locations that have been grouped in disaster-prone areas.
The conclusion of this research is that the application of disaster location information can help officers to handle things more quickly and prioritize areas that are at a high risk level for disasters.
References
Buku Kajian Risiko Bencana BPBD Kota Kediri : 2022
Liandi, A., & Andryawan, A. (2022). Penerapan Hukum Terhadap Penangkapan Ikan pada Wilayah Laut Indonesia Guna Menjaga Keberlanjutan Perikanan. PROSIDING SERINA, 2(1), 229-238.
Triana, D. (2017). Mitigasi bencana melalui pendekatan kultural dan struktural. ReTII.
Setiawati, Irma Yunita, Andreas Handojo, and Anita Nathania Purbowo. "Aplikasi Informasi Posko Bencana Alam Berbasis Android." Jurnal Infra 3.2 (2015): 297-302.
Burd, Barry, Michael Burton, and Donn Felker. Java and Android Application Development For Dummies eBook Set. John Wiley & Sons, 2012.
Cinar, Onur. Android apps with Eclipse. Apress, 2012.
SVENNERBERG, Gabriel. Beginning google maps API 3. Apress, 2010.
Putro, R., and Mustafa KAMAL. Analisis Pengaruh Brand Reputation, Brand Competence, dan Brand Liking Terhadap Trust In Brand Pada Konsumen Windows Phone Nokia di Surabaya. Diss. Fakultas Ekonomika dan Bisnis, 2013.
Sutabri, Tata. Konsep sistem informasi. Penerbit Andi, 2012.
Wahidah, Nilam, Oktalia Juwita, and Fajrin Nurman Arifin. "Pengelompokkan Daerah Rawan Bencana di Kabupaten Jember Menggunakan Metode K-Means Clustering." INFORMAL: Informatics Journal 8.1 (2023): 22-29.
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