INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi
Vol 5 No 2 (2021): August 2021

The Natural Disaster Prone Index Map Model in Indonesia Using the Thiessen Polygon Method

Kevin Hendra William (Universitas Kristen Satya Wacana)
Kristoko Dwi Hutomo (Universitas Kristen Satya Wacana)



Article Info

Publish Date
08 Aug 2021

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.

Copyrights © 2021






Journal Info

Abbrev

intensif

Publisher

Subject

Computer Science & IT Decision Sciences, Operations Research & Management

Description

INTENSIF Journal is a publication container for research in various fields related to information systems. These fields includeInformation System, Software Engineering, Data Mining, Data Warehouse, Computer Networking, Artificial Intelligence, e-Bussiness, e-Government, Big Data, Application ...