Analisis Tingkat Permukiman Kumuh Menggunakan Metode AHP Berbasis SIG pada Kota Magelang

Sastanti, Silvia Yolanda; Fibriani, Charitas

doi:10.25077/teknosi.v5i1.2019.69-78

Cited by 9 publications

(8 citation statements)

References 2 publications

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“…generated a pairwise comparison matrix (Fig. 2b) to validate whether the normalized relative weights align with geographical conditions and flood hazard causes at the research location (Yolanda et al, 2019). After obtaining the decision matrix, eigenvectors and consistency ratio (CR) are determined.…”

Section: Validation Of Ahp Modelsmentioning

confidence: 99%

“…The obtained consistency ratio is 4.8%, calculated from the maximum λ (or an estimated value). Although the CR value is relatively high (> 0.1) Yolanda et al, 2019), it falls into the "good" category according to the AHP calculator. Experts have different perceptions of the priority between one parameter and another due to differences in the variation of flooding that occurs in the Tuntang watershed.…”

Section: Validation Of Ahp Modelsmentioning

confidence: 99%

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2024

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Papua, known as one of the wettest regions in the world with annual precipitation ranging from 2400 to 4500 mm, faces a high risk of flooding, especially during La Niña, as observed in 2018 and 2022. Conversely, the region also experiences forest fires, mainly in the southern areas of Papua, during periods of extreme dry conditions brought about by El Niño events, as seen in 2002, 2004, and 2015. Given the increasing frequency of extreme climate events in the context of climate change, understanding the impact of global climate phenomena such as El Niño Southern Oscillation (ENSO) on Papua is crucial. This research aims to analyze the influence of ENSO and the Indian Ocean Dipole (IOD) on forest fires and flood risk in Papua, Indonesia. The analysis of forest fires utilizes MODIS hotspot and ERA5 precipitation data, employing quantitative modeling techniques such as Lasso and Elastic Net Regression. It integrates both ENSO and IOD indices into the precipitation indicators. In contrast, flood analysis is carried out through distribution and joint pattern analysis. The Elastic Net Regression yields promising results in modeling, with more than 96% of the tested models successfully predicting the total annual hotspots for each year, achieving an R-squared value of 90%. This suggests that the method and algorithm used can serve as a robust model for early hotspot prediction in the analyzed area. The warm phases of ENSO and IOD consistently exhibit a positive correlation with the dry season. However, the cold phases of these phenomena do not significantly impact heavy and extreme precipitation indicators in the studied region. The flood analysis reveals that La Niña has only a slight effect on all three precipitation patterns in the analyzed area, primarily by increasing the risk of extreme precipitation indicators. Conversely, negative IOD demonstrates inconsistency across all three precipitation patterns in Papua.

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Section: Validation Of Ahp Modelsmentioning

confidence: 99%

Section: Validation Of Ahp Modelsmentioning

confidence: 99%

Untitled

2024

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“…Kriteria dalam AHP untuk penentuan kawasan kumuh ditentukan dengan metode expert judgement atau dengan disepakati oleh para ahli yang berkompeten di bidangnya serta dengan mempelajari literatur-literatur dan jurnal-jurnal ilmiah yang terkait dengan penelitian ini. Menurut (Sastanti & Fibriani, 2019) kriteria yang sesuai untuk analisis pemukiman kumuh di Kota Magelang dengan penggunaan AHP adalah kondisi bangunan gedung, kondisi jalan, kondisi drainase, kondisi pengolahan air minum dan kondisi air limbah. (Mutaqin, 2017) dalam tulisannya tentang studi penentuan perioritas penanganan lingkungan permukiman kumuh menuju kampung berkelanjutan di kota Palembang menggunakan kriteria RTH (Ruang Terbuka Hijau), aspek lingkungan, aspek sosial dan aspek ekonomi.…”

Section: Pendahuluanunclassified

Pemetaan Kawasan Kumuh Menggunakan Metode AHP dan GIS di Kota Tanjungbalai

Nasution

Mulia

2021

JSA

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Kawasan kumuh yang terjadi di Kota Tanjungbalai dikarenakan salah satunya kurangnya kesadaran masyarakat di Kota Tanjungbalai sehingga sampai saat ini masih banyak lingkungan yang terindikasi kawasan kumuh yang sangat tinggi. Kawasan permukiman penduduk yang semakin padat dan kotor, kondisi jalan yang semakin buruk dan drainase yang penuh dengan sampah merupakan tanda-tanda kekumuhan. Untuk penanganannya perlu ada analisa terhadap faktor apa saja yang menyebabkan hal itu terjadi sehingga upaya penanganan dan pencegahan dapat tepat sasaran. Studi ini bertujuan menentukan kawasan berdasarkan ketertinggalan dan kekumuhan dengan beberapa tingkatan yaitu kawasan sangat tinggi, kawasan tinggi, kawasan sedang, kawasan rendah dan kawasan sangat rendah menggunakan metode AHP dan GIS. Penelitian ini dilakukan secara kualitatif dengan menggunakan mengumpulkan data primer dan sekunder yang kemudian akan diolah dengan metode AHP dan GIS. Kawasan yang berdasarkan ketertinggalan terdiri dari 4 kriteria dan 22 sub-kriteria sedangkan kawasan berdasarkan kekumuhan terdiri dari 1 kriteria dan 7 sub-kriteria. Dari hasil analisa diperoleh kawasan yang berdasarkan ketertinggalan yaitu: kawasan sangat tinggi 53 lingkungan, kawasan tinggi 69 lingkungan, kawasan sedang 45 lingkungan, kawasan rendah 13 lingkungan, dan kawasan sangat rendah 7 lingkungan dan kawasan berdasarkan kekumuhan maka diperoleh sebagai berikut: kawasan sangat tinggi 11 lingkungan, kawasan tinggi 90 lingkungan, kawasan sedang 68 lingkungan, kawasan rendah 14 lingkungan dan kawasan sangat rendah 11 lingkungan

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“…(Zaim, Rudiarto, Buchori, & Wahyudi, 2020). Aspects such as the condition of buildings/buildings, environmental roadways, environmental drainage, drinking water services, wastewater management, and waste management are all considered during physical handling activities (Sastanti & Fibriani, 2019). The development of effective policies for reducing the number of households that are chronically poor and the number of households that are at risk of falling into poverty, as well as for assisting households in escaping poverty, is facilitated by an understanding of the strategies employed by different groups of people living in poverty to make a living.…”

Section: Introductionmentioning

confidence: 99%

Criteria for Sustaining Coastal Communities' Livelihoods

Septanti

Santoso

Cahyadini

et al. 2023

IRSPSD International

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Karangsari Urban Village is one of the slum areas recognized in Tuban Regency in 2016. This is because Karangsari Village has a variety of environmental problems, including the highest building irregularity of any village at 300 units per hectare, particularly in areas bordering the beach; the habit of discarding garbage in the sea; and inadequate facilities for washing and toilets (Plan for Settlement of the Karangsari Urban Village Settlement Environment, 2018). As a result, changes were made to the region in 2018, transforming it from light slums to non-slums. However, it is well established from existing study that Karangsari Urban Village is unsustainable in terms of natural capital, physical capital, human capital, economic capital, and social capital. This study defines a set of sustainable livelihoods criteria to ensure that individuals achieve their basic requirements without compromising future generations. The analysis is quantitative, and the fishbone diagram is used to illustrate it. The research produced a set of criteria that must be completed in order for communities, leaders, and government to collaborate on developing sustainable livelihoods that are suited for village conditions. Coastal circumstances must be addressed in a way that balances the needs of nature and civilization, the community must actively participate in and suggest current development, and financial institutions for local communities must be available (both formal and informal).

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Analisis Tingkat Permukiman Kumuh Menggunakan Metode AHP Berbasis SIG pada Kota Magelang

Cited by 9 publications

References 2 publications

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Pemetaan Kawasan Kumuh Menggunakan Metode AHP dan GIS di Kota Tanjungbalai

Criteria for Sustaining Coastal Communities' Livelihoods

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