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All Journal Jurnal Geografi El-Jughrafiyah : Jurnal Geografi dan Terapannya
Al Kautsar, Azhari
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Earth & Planetary Sciences Education Environmental Science Physics Social Sciences Other

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Model Spasial Prediktif Bahaya Bullying di Kota Depok Al Kautsar, Azhari; Manurung, Parluhutan
EL-JUGHRAFIYAH Vol 5, No 2 (2025): El-Jughrafiyah : August, 2025
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/jej.v5i2.36357

Abstract

Tujuan dari penelitian ini adalah untuk memprediksi spasial tingkat bahaya bullying di Kota Depok. Kemudian tujuan lainnya adalah seberapa penggunaan data lokasi pendidikan terhadap potensi prediksi kekerasan bullying pada usia remaja di Kota Depok. Metodologi penelitian ini menggunakan analisis multi-kriteria (AHP), kriging, regresi OLS, REML, PLS, GB, RF, dan INLA. Temuan utama pada penelitian ini adalah terjadi perbedaan pengukuran model spasial prediktif yang dikatakan tinggi seperti krigring, GB, REML, dan INLA demikian juga yang terendah seperti PLS dan RF. Temuan berikutnya dari model spasial prediktif tingkat bahaya bullying tercermin dari lokasi kegiatan pelajar usia remaja seperti pendidikan, kegiatan hiburan remaja, pemerintah dan keamanan, fasilitas kesehatan, dan tempat ibadah. Kesimpulan yang diperoleh dalam penelitian ini adalah keseluruhan tingkat bahaya bullying tinggi dengan nilai 0,6 – 0,8.
Monitoring Aerosol Optical Depth for Air Quality Through Himawari-8 in Urban Area West Java Province Indonesia Ridwana, Riki; Himayah, Shafira; Rabbi, Muh Fiqri Abdi; Ahmad Lugina, Izma Maulana; Al Kautsar, Azhari; Sakti, Anjar Dimara
JURNAL GEOGRAFI Vol. 15 No. 2 (2023): JURNAL GEOGRAFI
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/jg.v15i2.36866

Abstract

Air quality is a crucial parameter in human life. One air quality indicator can be observed through Aerosol Optical Depth (AOD). If these substances are pollutants such as particulate matter, aerosols, and ozone, it is confident that air quality will deteriorate, threatening human health and causing climate change. AOD monitoring can be used as a basis for policymakers and related parties to maintain the stability of air quality in the atmosphere. Many ground observation stations monitor air quality by obtaining data on PM2.5 and PM10 aerosol particles. However, the number of ground stations is limited, resulting in incomplete data. Fortunately, remote sensing satellites have the advantage of covering large areas and providing continuous observations, with the ability to gather information on large-scale aerosol and obtain spatiotemporal distribution. Therefore, this research aims to obtain AOD through Himawari-8 and analyze the spatiotemporal air quality in urban areas of West Java based on AOD. The research methodology used in this study is descriptive analysis with an empirical research approach. Assisted by remote sensing technology and Geographic Information Systems, this research generates AOD data extraction that can be obtained from the new generation satellite of Himawari-8. The distribution of AOD levels and spatiotemporal monitoring in urban areas of West Java is very dynamic depending on anthropogenic activity in a particular area and time. Keywords: Aerosol Optical Depth (AOD), Air Quality, Himawari-8
Detection of Urban Landscape Changes in Surabaya for the Years 2014-2024 Based on NDVI and NDBI Analysis of Landsat 8 OLI Imagery Widiastuti, Rastika; Wijaya, Muhammad Sufwandika; Al Kautsar, Azhari; Widiana Putri, Inanditya; Kusratmoko, Eko
JURNAL GEOGRAFI Vol. 17 No. 1 (2025): JURNAL GEOGRAFI
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/jg.v17i1.59320

Abstract

This study investigates urban landscape changes in Surabaya from 2014 to 2024 using NDVI and NDBI indices derived from Landsat 8 OLI imagery. The Earth Engine platform was employed to generate cloud-free composite images, enabling detailed analysis of vegetation and built-up area changes. The methodology included a bivariate geovisualization technique to display areas of change, comparing NDVI and NDBI values over a decade to assess changes at a granular level. Results indicate that the 'Vegetation Stable - Built-up Area Stable' category dominates, covering 2422 km², suggesting consistent land use in established areas. This dominance indicates well-established land use patterns across much of the city. Significant urbanization is observed in the 'Vegetation Decreased - Built-up Area Increased' (70 km²) and 'Vegetation Stable - Built-up Area Increased' (177 km²) categories, reflecting ongoing development pressures. These areas highlight zones of active development and environmental intervention. Additionally, a 75 km² increase in vegetation, particularly in coastal mangrove regions, highlights successful environmental management efforts. The study achieved an overall accuracy of 71%, demonstrating the effectiveness of NDVI and NDBI in capturing urban dynamics. While some classes require improved detection accuracy, particularly those involving decreased built-up areas, the model reliably identifies increases in vegetation and built-up areas.
Co-Authors Ahmad Lugina, Izma Maulana Eko Kusratmoko Himayah, Shafira Muhammad Sufwandika Wijaya Parluhutan Manurung Rabbi, Muh Fiqri Abdi Ridwana, Riki Sakti, Anjar Dimara Widiana Putri, Inanditya Widiastuti, Rastika