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All Journal INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi
Kevin Hendra William
Universitas Kristen Satya Wacana
Computer Science & IT Decision Sciences, Operations Research & Management

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The Natural Disaster Prone Index Map Model in Indonesia Using the Thiessen Polygon Method Kevin Hendra William; Kristoko Dwi Hutomo
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 5 No 2 (2021): August 2021
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (506.786 KB) | DOI: 10.29407/intensif.v5i2.14612

Abstract

Natural Disasters are natural phenomena that occur at any moment that can cause loss. Indonesia is an archipelagic country located at the meeting of four tectonic plates and volcanic belts. This condition causes Indonesia to be prone to natural disasters. Therefore, it is necessary to make a natural disaster-prone index map model minimize the impact of natural disasters. In this research, the researchers used a Polygon Thiessen method for it was one of the mapping methods to determine a natural disaster based on Indonesia's vast surface and many disasters. The BNPB and Polygon Thiessen data comparison shows that BNPB data has a low level of vulnerability of 302, a moderate level of vulnerability of 148, and a high level of vulnerability of 58. In contrast, the Thiessen polygon has a low level of vulnerability of 297, a moderate vulnerability of 158, and a high vulnerability of 59. Comparing BNPB data and the Thiessen Polygon method found five differences from 40 data in the Papua region. Suggestions for further research to create an application-based information system so that it can be accessed in real-time.
Co-Authors Kristoko Dwi Hartomo