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KAJIAN POLA KESENJANGAN EKONOMI WILAYAH DI KAWASAN AGLOMERASI MALANG RAYA Widiyanto Widodo; Annisaa Hammidah Imadudinna; Agustina Nurul Hidayati
Jurnal Plano Buana Vol 3 No 2 (2023): Jurnal Plano Buana (Edisi April 2023)
Publisher : Program Studi Perencanaan Wilayah dan Kota, Universitas PGRI Adi Buana Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36456/jpb.v3i2.6801

Abstract

Kondisi dan potensi setiap wilayah sangat beragam dengan karakteristik masing- masing. Hal ini menjadikan tingkat tumbuh dan berkembangnya suatu wilayah menjadi berbeda- beda. Karena perbedaan kondisi wilayah sehingga tingkat tumbuh dan berkembangnya wilayah menjadi berbeda maka kondisi ini menyebabkan terjadinya ketidakmerataan kecepatan pengembangan dan pembangunan wilayah atau yang disebut disparitas/kesenjangan. Kesenjangan akan menjadi masalah bila terjadi kesenjangan yang terlalu besar dan disebabkan oleh sistem pembangunan yang salah, sehingga dapat menjadi penyebab munculnya keresahan, ketidakpuasan dan bahkan sampai timbul aksi dari sekelompok masyarakat untuk memisahkan diri dari NKRI. Permasalahan mendasar pada pengembangan wilayah di Kawasan Metropolitan terutama Malang Raya adalah kesenjangan antara daerah dimana pembangunan di monosentris, terpusat pada Kota Malang. Menanggapi kondisi demikian, dibutuhkan perumusan pola kesenjangan wilayah di Malang Raya, untuk mengetahui sejauh mana pemusatan pembangunan dan pertumbuhan wilayah di Malang Raya. Selain itu diharapkan melalui perumusan pola kesenjangan wilayah mampu menjadi acuan sehingga arahan dapat meminimalkan kesenjangan wilayah di Malang Raya. Penelitian terkait pola kesenjangan ekonomi wilayah ini berlokasi di Malang Raya yang terdiri dari 3 wilayah yaitu Kota Malang, Kabupaten Malang dan Kota Batu. metode analisa yang digunakan adalah LISA (Local Autocorrelation). Dari hasil Local Indicator Of Spatial Association (LISA) bahwa kabupaten Malang High-low mengelilingi daerah kota Malang dan Kota Batu low-high, artinya belum ada kesenjangan di wilayah Kota Batu dan kota Malang namun kesenjangan wilayah di Kabupaten Malang.
Kesesuaian Daya Dukung Lingkungan terhadap Mitigasi Kawasan Permukiman Kumuh di Perkotaan Banyuwangi Setiawati, Hendri; Hidayati, Agustina Nurul; Rusdiyanto, Edi
Jurnal Ilmiah Universitas Batanghari Jambi Vol 25, No 1 (2025): Februari
Publisher : Universitas Batanghari Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33087/jiubj.v25i1.5804

Abstract

The purpose of this study is to analyze the suitability of environmental carrying capacity in slum areas in Banyuwangi City and to develop a mitigation concept for slum areas in Banyuwangi City. The method used is an overlay analysis of environmental carrying capacity to assess the suitability of environmental carrying capacity and the Analysis Hierarchy Process (AHP) to determine the priority of mitigation steps based on seven slum indicators. The results of the study showed that around 81% of slum areas in Banyuwangi City were assessed as being in accordance with environmental carrying capacity, while the other 19% were not in accordance in almost all villages with the largest area, namely Sobo Village.
URBAN ORGANISATION AREA MITIGATION STRATEGY BASED ON ENVIRONMENTAL CARRYING CAPACITY IN THE BANYUWANGI SUB-DISTRICT Setiawati, Hendri; Hidayati, Agustina Nurul; Rusdiyanto, Edi
Journal of Sustainable Technology and Applied Science (JSTAS) Vol. 6 No. 1 (2025): Journal of Sustainable Technology and Applied Science, May 2025
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat, Institut Teknologi Nasional (ITN) Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jstas.v6i1.11730

Abstract

Urban organisational areas are often influenced by economic activities that increase housing demand, both from the workforce and residents. This also occurs in Banyuwangi District, which serves as the Regional Activity Centre (PKW) with port, industrial, trade, and infrastructure activities. However, some areas, such as Karangrejo Village and Sobo Village, have slum organisational areas. This study aims to identify the mismatch of environmental carrying capacity in the organizational area of ​​Banyuwangi District and to develop mitigation strategies based on environmental carrying capacity. The methods used include environmental carrying capacity analysis, land uniformity, and SWOT analysis. The results indicate that the demographic carrying capacity in the area is low, particularly due to the air resource deficit in Kampung Melayu, Panderejo, and Temenggungan Villages. Kampungmelayu, Kertosari, and Sobo Villages also face similar problems related to organisational carrying capacity. The analysis reveals that 1% of the area is not permanently suitable, including sub-districts such as Kampungmandar, Karangrejo, and Kepatihan, while the remaining 5% of the area is currently unsuitable. Only 30% of the area is considered suitable for environmental carrying capacity. Then, to find out the strategy, a SWOT analysis was carried out, which can recommend a progressive strategy (growth-oriented strategy) that focuses on developing the trade, service, tourism, and cultural sectors based on environmental carrying capacity, as well as providing basic residential infrastructure and disaster mitigation training.
Land Use Predictions to the Response of Kediri Airport Imadudina, Annisaa Hammidah; Widodo, Widiyanto Hari Subagyo; Hidayati, Agustina Nurul
Jurnal Spatial Wahana Komunikasi dan Informasi Geografi Vol. 22 No. 1 (2022): Spatial : Wahana Komunikasi dan Informasi Geografi
Publisher : Department Geography Education Faculty of Social Science - Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/spatial.221.1

Abstract

Kediri Regency is a district with sufficient development with the existence of PSN for the construction of Kediri Airport. Kediri Airport was finally designated as PSN. This Rp 10 trillion airport is included in PSN in accordance with Presidential Regulation Number 56 of 2018. After Kediri Airport, Immediately Build the Kertosono-Tulungagung Toll Road. Land Acquisition for the Kediri Section is Completed in 2021. With this national strategic project, investment development in Kediri Regency will definitely increase. Based on the above, it is very necessary to predict future land use to be able to know the response of land use to the integrated airport and toll road project. The methods used in this research are remote sensing, GIS analysis, cellular automata analysis and descriptive analysis. Knowing the spatial response will be a very meaningful input for planners, especially in formulating plans to maximize the multiplier effect caused by the airport and toll roads on the surrounding space.
DINAMIC MODELING OF SOCIO – ECONOMIC ACTIVITY CHANGES AROUND THE PANDAAN – MALANG TOLLL GATE USING NIGHT TIME LIGHT AND ANALYSIS MACHINE LEARNING Parmanes, Ester; Hidayati, Agustina Nurul; Witjaksono, Agung; Afrianto, Firman
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 8 No. 2 (2025): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jtsi.v8i2.54049

Abstract

The study of the Pandaan–Malang Toll Road development is relevant for understanding the impact of infrastructure on socio-economic changes based on spatial data. To date, quantitative approaches that combine satellite imagery data with artificial intelligence algorithms have rarely been used comprehensively to assess regional dynamics. This study develops a machine learning-based prediction model to examine the relationship between infrastructure development and the intensity of community activities. The primary data analyzed is Night-Time Light (NTL) from satellite observations, which is treated as an indicator of the level of economic and social activity on the earth's surface. The research stages include the process of extracting and transforming spatial data, temporal analysis of night light intensity from 2013 to 2023, and the application of the Random Forest algorithm to predict trends until 2040. The findings indicate that areas adjacent to the toll gate show a consistent increase in night light intensity, reflecting faster growth in economic activity and population density compared to other areas. The developed prediction model demonstrates high performance with a low mean squared error (MSE) value. The integration of NTL data and the machine learning approach has proven to be able to describe spatial dynamics more objectively and precisely. Scientifically, this study introduces a replicable analytical framework to support evidence-based decision-making in infrastructure planning and sustainable regional development.