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All Journal Indonesian Journal of Geography Geoplanning : Journal of Geomatics and Planning Jurnal Tata Kota dan Daerah Jurnal Wilayah dan Lingkungan JPG (Jurnal Pendidikan Geografi) MAJALAH ILMIAH GLOBE Jurnal Geografi Jurnal Reksabumi: Journal of Urban , Regional, and, Environmental Planning Jurnal Ilmiah Sistem Informasi
Aryaguna, Prama Ardha
Universitas Esa Unggul
Civil Engineering, Building, Construction & Architecture Computer Science & IT Earth & Planetary Sciences Education Engineering Environmental Science Social Sciences Transportation Other

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Analysis of Population Growth Trends Based on Geographic Information Systems in East Jakarta Aryaguna, Prama Ardha
Indonesian Journal of Geography Vol 57, No 1 (2025): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijg.98644

Abstract

The increase in population is accompanied by equal distribution. In this context, population density of Jakarta is partly due to urbanization and long-term settlement. Therefore, this research is carried out to identify sub-districts experiencing the fastest population growth and the accommodated capacity. Population issues must be a central point of sustainable development allowing every resident and future generations to live healthily, prosperously, productively, and harmoniously with the environment. The relationship between population growth rate (PGR) and spatial aspects such as healthcare facilities, trade facilities, transportation facilities, government offices, education facilities, industry, and the availability of residential buildings from 2017 to 2022 is determined through Geographic Information System (GIS)-based analysis using statistical methods. The trend of PGR in East Jakarta sub-districts is high in the northwest and north, bordering Central and North Jakarta. Meanwhile, spatial aspects influencing high population growth are the availability of residential buildings and schools. Increased residential buildings and public schools in a sub-district due to the zoning policy in student enrollment are directly proportional to population growth.Received: 2024-07-27 Revised: 2024-10-18 Accepted: 2025-01-30 Published: 2025-02-12  
Modeling of Land Cover Changes in Banjarbaru City South Kalimantan Province Saputra, Aswin Nur; Saputra, Muhammad Wahyu; Fatchurohman, Hendy; Aryaguna, Prama Ardha
JURNAL GEOGRAFI Vol. 16 No. 1 (2024): JURNAL GEOGRAFI
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/jg.v16i1.48121

Abstract

Urban areas often experience land cover changes. Banjarbaru is one of several cities in Indonesia that has experienced land changes. The relocation of the administrative center of Banjarmasin City to Banjarbaru City led to the development of settlements. One spatial analysis carried out to examine the phenomenon of land change is remote sensing techniques. The method that can be used is the Land Change Modeler from MOLUSCE in QGIS. This model uses the CAM (Cellular Automata Markov) method to identify land cover change and predict land cover distribution. CAM can understand and predict land change patterns by considering land use, vegetation, and cell spatial interactions. This modeling is based on land cover data for 2015 and 2020 and several supporting parameters such as DEM data and distance to roads. Based on the modeling results from 2015 and 2020, Banjarbaru City experienced a change in built-up land, with most of it occurring in the center of Banjarbaru City. Based on the Markov Chain method by looking at land changes in the previous year, the development of built-up land increased by about 8% of the Banjarbaru City area of 32917.41 hectares. Based on the prediction results, the development of built-up land is centered in the middle of Banjarbaru City, such as North and South Banjarbaru Districts, due to the development of residential development.Keywords: Land Cover, Land Change Modeller, Cellular Automata, Markov Chain
Analisis Hubungan Sebaran Ruang Terbuka Hijau dan Kepadatan Bangunan Terhadap Intensitas Suhu Permukaan Tanah di Jakarta Timur Tahun 2022 Hasanudin, Hasanudin; Sari, Dayu Ariesta Kirana; Setyaningrum, Nugraheni; Cahya, Darmawan Listya; Aryaguna, Prama Ardha
Jurnal Wilayah dan Lingkungan Vol 13, No 2 (2025): Agustus 2025
Publisher : Department of Urban and Regional Planning, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jwl.13.2.117-134

Abstract

Pertumbuhan penduduk yang tinggi dengan padatnya bangunan di perkotaan, disertai dengan kurangnya RTH menyebabkan kenaikan suhu permukaan di perkotaan. Jakarta Timur merupakan Kota Jakarta Timur, salah satu kota dengan pertumbuhan penduduk di tertinggi dalam satu dekade terakhir, sehingga mengalami perubahan penggunaan lahan dengan meningkatnya kepadatan bangunan dan berkurangnya RTH di perkotaan. Penelitian ini bertujuan untuk mengetahui menganalisis bagaimana persebaran RTH dan kondisi kepadatan bangunan serta hubungannya dengan intensitas suhu permukaan tanah di Jakarta Timur. Data yang digunakan diperoleh dari pengolahan citra Landsat 8 dengan algoritma NDBI (Normalized Difference Built-up Index), NDVI (Normalized Difference Vegetation Index), dan LST (Land Surface Temperature). Analisis korelasi dan regresi dilakukan untuk mengetahui hubungan antara NDBI, NDVI dan LST. Hasil penelitian menunjukkan bahwa komposisi Ruang Terbuka Hijau (RTH) di Jakarta Timur mencakup 58% vegetasi rendah, 22% vegetasi sedang, dan 19% vegetasi tinggi, dengan sebaran RTH yang lebih signifikan di daerah peri-urban. Sedangkan untuk kepadatan bangunan menunjukkan  kepadatan rendah 8%, kepadatan sedang 51% dan kepadatan tinggi 16%. Ditinjau dari penggunaan lahannya didominasi sebagai hunian, dengan rata – rata kepadatan bangunan dalam klasifikasi sedang. Suhu permukaan tanah rata-rata di tiap kecamatan di Jakarta Timur sebesar 26,02°C. Berdasarkan hasil analisis diketahui kenaikan LST dipengaruhi oleh nilai NDBI dan nilai NDVI dengan nilai korelasi 0,7454 serta koefisien determinasi (R2) sebesar 0,556. Untuk persamaan regresi yang dihasilkan yaitu Y=26,73-2,558X1+4,795X2+0,02.
Co-Authors Ade Arianto Aswin Nur Saputra Aswin Nur Saputra Darmawan Listya Cahya Dayu Ariesta Kirana Dayu Ariesta Kirana Sari Fatchurohman, Hendy Gaffara, Ghefra Rizkan Hasanudin Hasanudin Hendy Fatchurohman Horas Maulite Andrey Gromiko Horas Maulite Andrey Gromiko Kartika Pratiwi Kurniawan, Surya Muhammad Sufwandika Wijaya Muhammad Wahyu Saputra Nurhaidar, Wa Ode Primasmada, Danny Projo Danoedoro Rudiastuti, Aninda Wisaksanti Sanjiwana Arjasakusuma Saputra, Muhammad Wahyu Sari, Dayu Ariesta Kirana Setyaningrum, Nugraheni Sigit Heru Murti Suryandari, Ratnawati Widyawati, Laili Fuji Yanuar Adji Nugroho Yohan, Mohamad