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Record W4411375236 · doi:10.18280/ijsdp.200503

Application of Flood Modeling in Informal Settlement Areas in Makassar City, Indonesia

2025· article· en· W4411375236 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2025
Typearticle
Languageen
FieldComputer Science
TopicMultimedia Learning Systems
Canadian institutionsnot available
Fundersnot available
KeywordsSettlement (finance)Flood mythGeographyEnvironmental planningCivil engineeringArchaeologyWater resource managementEnvironmental scienceEngineeringBusiness

Abstract

fetched live from OpenAlex

The Spatial and Regional Plan (RTRW) of Makassar City 2015-2034 does not cover the Mariso and Mamajang Sub-districts in flood-prone areas, even though both districts have experienced flooding.To investigate this issue, this research focuses on flood modeling-based flood modeling.The aim of this research is to identify the existing spatial conditions in the research area by conducting flood simulation modeling in both districts and analyzing the spatial impact of flood modeling on informal settlement areas.The research was conducted over four months, from April to July 2023.The data used includes primary and secondary data obtained from government agencies and field observations.Spatial data includes actual flood areas, land cover, and DEM-NAS, while non-spatial data involves rainfall and tidal data.The research methods include qualitative and quantitative analyses.Spatial analysis is used to analyze the distribution of flood areas, elevation conditions, rainfall, land cover, informal settlement areas, and flood model maps.Meanwhile, quantitative analysis involves data analysis in tabulation and graphs, such as rainfall intensity, tidal data, Manning's roughness coefficient, runoff values, and the number of pixels in the flood model.The research results include four main pieces of information: an existing area analysis identifying 125 flood areas.The elevation of the coastal area is generally low, with the highest elevation on land reaching 23 meters.There are 11 types of land cover, and rainfall falls into the moderate to high category.Flood modeling results in macro and micro, simulations in terms of water levels and flood flow.Validation results show a modeling accuracy level of 69.03%.Meanwhile, the spatial impact of flood modeling results in 60 flood distribution areas with varying heights between 10 cm and 300 cm, with informal settlement areas behind the most affected.This research provides information to understand the flood characteristics in informal settlements in the Mariso and Mamajang Sub-districts of Makassar City through a comprehensive flood modeling-based approach.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.532
Threshold uncertainty score0.317

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.269
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it