Riyanovita Kautsar Maulida Nisaa', - and Lili Somantri, - and Silmi Afina Aliyan, - (2025) ANALISIS TINGKAT PERMUKIMAN KUMUH BERBASIS VISIBLE GREEN-BASED BUILT-UP INDICES (VGNIR- BI) CITRA SPOT 6 MENGGUNAKAN METODE OBJECT-BASED IMAGE ANALYSIS (OBIA) DI KOTA BANDUNG BAGIAN BARAT. S1 thesis, Universitas Pendidikan Indonesia.
Abstract
Fenomena urbanisasi yang meningkat setiap tahunnya memunculkan berbagai permasalahan salah satunya permukiman kumuh. Pemetaan karakteristik tingkat permukiman kumuh sebagai langkah awal dalam mencapai peningkatan kualitas permukiman kumuh. Tujuan penelitian ini untuk mengetahui sebaran, tingkat dan pola permukiman kumuh di Kota Bandung bagian barat memanfaatkan Citra SPOT 6 dengan metode Object-Based Image Analysis (OBIA) didukung oleh algoritma Visible Green-Based Built-Up Indices (VGNIR- BI) untuk melihat tingkat kerapatan bangunan. Pengolahan sebaran dan luasan permukiman kumuh menghasilkan klasifikasi berupa non permukiman, tidak kumuh dan kumuh dengan luasan wilayah permukiman kumuh tersebar di 5 kecamatan yaitu kecamatan Cicendo, Andir, Bandung Kulon, Babakan Ciparay, dan Bojongloa Kaler dengan luas kumuh terbesar yaitu Kecamatan Bojongloa Kaler sebesar 56,43 % dari total luas wilayah tersebut, sebaliknya wilayah dengan luasan permukiman kumuh terkecil menunjukan wilayah Kecamatan Cicendo hanya sekitar 16,75% dari total luas wilayahnya. Tingkat permukiman kumuh di Kota Bandung bagian barat yang mendominasi yaitu tingkat permukiman kumuh ringan seluas 616,95 ha atau 21,57% dari 2860,72 ha total luas wilayahnya dengan pola permukiman kumuh di Kota Bandung bagian barat cenderung mengelompok. Nilai akurasi pengolahan metode OBIA menghasilkan overall accuracy sebesar 88% dengan Kappa accuracy sebesar 83% hal ini menunjukan bahwa metode Object-Based Image Analysis (OBIA) mampu memberikan hasil yang cukup baik dalam menentukan klasifikasi tingkat permukiman kumuh berdasarkan objek. The phenomenon of urbanization that increases every year gives rise to various problems, one of which is slums. Mapping the characteristics of slum levels as an initial step in achieving improved quality of slums. The purpose of this study is to determine the distribution, level and pattern of slums in the western part of Bandung City using SPOT 6 Imagery with the Object-Based Image Analysis (OBIA) method supported by the Visible Green-Based Built-Up Indices (VGNIR-BI) algorithm to see the level of building density. The processing of the distribution and area of slum settlements produces a classification in the form of non-slums, non-slums and slums with the area of slum settlements spread across 5 sub-districts, namely Cicendo, Andir, Bandung Kulon, Babakan Ciparay, and Bojongloa Kaler sub-districts with the largest slum area being Bojongloa Kaler Sub-district of 56.43% of the total area, conversely the area with the smallest slum area shows the Cicendo Sub-district area of only around 16.75% of the total area. The level of slum settlements in the West Bandung City that dominates is the level of light slum settlements covering an area of 616.95 ha or 21.57% of the total area of 2860.72 ha with a pattern of slum settlements in the West Bandung City tending to be clustered. The processing accuracy value of the OBIA method produces an overall accuracy of 88% with a Kappa accuracy of 83%. This shows that the Object-Based Image Analysis (OBIA) method is able to provide quite good results in determining the classification of slum levels based on objects.
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| Item Type: | Thesis (S1) |
|---|---|
| Additional Information: | https://scholar.google.com/citations?hl=en&authuser=1&user=8Lj-oQUAAAAJ ID SINTA Dosen Pembimbing: Lili Somantri: 5995390 Silmi Afina Aliyan: 6749474 |
| Uncontrolled Keywords: | Permukiman kumuh, Penginderaan Jauh, Object-Based Image Analysis (OBIA), Visible Green-Based Built-Up Indices (VGNIR-BI). Slums, Remote Sensing, Object-Based Image Analysis (OBIA), Visible Green-Based Built-Up Indices (VGNIR-BI). |
| Subjects: | G Geography. Anthropology. Recreation > G Geography (General) G Geography. Anthropology. Recreation > GF Human ecology. Anthropogeography G Geography. Anthropology. Recreation > GN Anthropology |
| Divisions: | Fakultas Pendidikan Ilmu Pengetahuan Sosial > Sains Informasi Geografi |
| Depositing User: | Riyanovita Kautsar Maulida Nisaa' |
| Date Deposited: | 24 Apr 2025 08:46 |
| Last Modified: | 24 Apr 2025 08:46 |
| URI: | http://repository.upi.edu/id/eprint/132456 |
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