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All Journal Journal of Degraded and Mining Lands Management Calamity: A Journal of Disaster Technology and Engineering
Rahardjo , Noorhadi
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Control & Systems Engineering Earth & Planetary Sciences Electrical & Electronics Engineering

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Mangrove area degradation and management strategies in Indonesia: A review Utami, Westi; Sugiyanto, Catur; Rahardjo , Noorhadi
Journal of Degraded and Mining Lands Management Vol. 11 No. 3 (2024)
Publisher : Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15243/jdmlm.2024.113.6037

Abstract

Coastal communities are particularly vulnerable to the effects of climate change. This study aimed to review the impact of land use change and mangrove degradation on coastal areas and analyze the problems and strategies of mangrove management in Indonesia. Journal data sources were obtained from the Scopus and Google Scholar databases. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method was used in the study. The results indicate that economic activities such as mining, industry, and ponds are the main cause of mangrove damage, which in turn leads to increased disasters, CO2 emissions, and decreased community income. To address this issue, mangrove management strategies that take into account social, economic, and environmental factors are necessary. Successful mangrove restoration requires increased inclusion, community capacity, budgeting, and stakeholder involvement. Government policies regulating sustainable spatial planning, law enforcement, and institutional frameworks are crucial components of mangrove management. The study's results are expected to serve as the foundation for developing sustainable coastal management strategies that enhance the safety of coastal communities from disasters and improve their welfare.
Visualizing 2018 lombok earthquake in Indonesia using crowdsouring data: How people experience it Aunurrahim, Abghy; Rahardjo , Noorhadi
Calamity: A Journal of Disaster Technology and Engineering Vol. 1 No. 1: (July) 2023
Publisher : Institute for Advanced Science, Social, and Sustainable Future

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61511/calamity.v1i1.2023.159

Abstract

Along with the development of science and technology, using big data, map makers can take advantage of crowdsourcing social media data on Twitter to obtain user location when uploading tweets, which can be called geolocated tweets. Earthquakes that occur very often in Indonesia often grab people's attention, especially netizens who use social media like Twitter. One of the major earthquakes that occurred in Indonesia in 2018 was the Lombok earthquake, which occurred twice in a row from July to August 2018. Using Twitter data, information and social responses related to the 2018 Lombok earthquake can be obtained, which can be used as evaluation material for public handling and responding. The information is then visualized in various forms, and one of the best visualization methods is selected.This study uses Twint package in Python as a way of obtaining location data from Twitter. The method used to collect Twitter data is a case study on the social impact of the Lombok earthquake in Indonesia in 2018. The data observation method used is a simulation of several types of map visualization and survey methods in selecting the best type of visualization. The method of analysis used is by mapping the data on the number of tweets as the main object using various types of maps, as well as calculating survey results by scoring each group of questions.The results of spatial data extraction from Twitter in this study obtained 2032 tweets that had been selected and cleaned from 11,584 tweets. Map visualization with the theme of the social impact of the Lombok earthquake in 2018 was compiled using five types of visualization, namely choropleth maps, proportional symbol maps, dot maps, hexagonal tessellation maps, and heat maps. Based on the results of the survey on selecting the best visualization, it was found that the choropleth map is the best visualization method according to respondents with a cartography background and respondents who are unfamiliar with cartography because the information displayed is easier to read and understand.
Co-Authors Aunurrahim, Abghy Catur Sugiyanto Westi Utami