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Sistem Peringatan Dini Rawan Bencana Longsor Di Kota Ambon menggunakan IoT

*Chrisdano Ryan Chandra Dasmasela  -  Universitas Kristen Satya Wacana, Indonesia
Irwan Sembiring  -  Universitas Kristen Satya Wacana, Indonesia
Hindriyanto Dwi Purnomo  -  Universitas Kristen Satya Wacana, Indonesia
Open Access Copyright (c) 2020 JSINBIS (Jurnal Sistem Informasi Bisnis)

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Abstract

Landslide disasters not only cause property losses but also have a multidimensional impact, for example people's psychology becomes disrupted, relocation of residential settlements and even disruption of investment as capital for economic development in Ambon City. This research aims to design a early warning system for landslide prone disastersin Ambon city and analysis using IoT.The results of the analysis use satellite landsat imagery as supporting spatial data with overlay indicators for landslide causes, including: rainfall, soil type, slope, population and land cover combined with placing IoT devices in landslide prone areas resulting in an early warning system for landslides. This IoT device uses a soil moisture sensor to read soil moisture and an MPU6050 accelerometer sensor to read soil movements. The results of the two sensors if they meet the criteria for landslide prone will be processed and sent as a notification to the smartphone. This research produces a landslide detection system starting from the analysis of landslide hazard maps to using sensors to detect landslide symptoms and then sending notification as a danger sign.

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Keywords: GIS; IoT; Landslide; Early Warning System.

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  1. Arifin, S., Carolina, I., Winarso, C., 2006. Implementasi penginderaan jauh dan SIG untuk inventarisasi daerah rawan bencana longsor. Jurnal Penginderaan Jauh Dan Pengolahan Data Citra Digital 3,77–86
  2. Artha, O.O., Rahmadya, B., Putri, R. E., 2018. Sistem peringatan dini bencana longsor menggunakan sensor accelerometer dan sensor kelembabapan tanah berbasis android. JITCE (Journal of Information Technology and Computer Engineering) 2 (02), 64–70
  3. Candra, J.E., Maulana, A., 2019. Penerapan soil moisture sensor untuk desain system penyiram tanaman otomatis. SNISTEK (2), 109–14
  4. Fitriani, P.N., Kusumawati, D.L., Handyesa, D.P., Madlazim., 2019. Rancang bangun prototipe deteksi dini tanah longsor berbasis double sensor. Jurnal Inovasi Fisika Indonesia (IFI) 08 (02) , 50–58
  5. Indrasmoro, G.P., 2013. Geographic Information System (GIS) untuk deteksi daerah rawan longsor studi kasus di Kelurahan Karang Anyar Gunung Semarang. Jurnal GIS Deteksi Rawan Longsor. 1–11
  6. Kasrani, M.W., Widyanto, G., 2016. Perancangan Prototype pengendali relay berbasis web dengan Ardino Uno dan Ethernet Shield. JTE UNIBA 1 (1), 22–27
  7. Kesaulya, H.M., Poli, H., Takumansang, E.D., 2016. Perencanaan Mitigasi Bencana Longsor Di Kota Ambon. Spasial 3 (3), 228–35
  8. Mardiyansyah., 2018. Peran Internet of Things (IoT) dalam penggulangan bencana Role of Internet of Things in Disaster Management. Jurnal Manajemen Projek ICT Magister Teknik Elektro Universitas Indonesia 1–7
  9. Muntohar, A.S., 2010. Tanah longsor: analisis-prediksi-mitigasi. Universitas Muhammadiyah Yogyakarta : Geotechnical Engineering Research Group (GERG)
  10. Taufik, M., Kurniawan, A., Putri, A.R., 2016. Identifikasi daerah rawan tanah longsor menggunakan SIG (Sistem Informasi Geografis) (Studi Kasus : Kabupaten Kediri). Jurnal Teknik ITS 5 (2)

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