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All Journal Majalah Geografi Indonesia Jurnal Geografi Jurnal Geografi LIngkungan Tropik (Journal of Geography of Tropical Environments)
Widiastuti, Rastika
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Earth & Planetary Sciences Education Environmental Science Social Sciences Other

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Penggunaan Data Sistem Lahan Skala 1 : 50.000 untuk Pemetaan Rawan Longsor di Kabupaten Majalengka Widiastuti, Rastika; Khairullah, Muhammad Qabus Abid; Tambunan, Mangapul Parlindungan; Wijaya, Muhammad Sufwandika
Majalah Geografi Indonesia Vol 39, No 1 (2025): Majalah Geografi Indonesia
Publisher : Fakultas Geografi, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/mgi.96138

Abstract

Abstrak. Penelitian ini mencoba mengoptimalkan pemanfaatan data sistem lahan untuk mengidentifikasi daerah rawan bencana tanah longsor di Kabupaten Majalengka. Data kejadian longsor dan peta sistem lahan digunakan sebagai sumber data utama, dengan fokus meihat pola kejadian longsor pada setiap unit sistem lahan. Metode analisis tumpang susun antara peta sistem lahan dan data kejadian longsor dikombinasikan dengan analisis geomorfologi digunakan untuk mengklasifikasikan tingkat kerawanan longsor. Hasilnya menunjukkan bahwa wilayah dengan sistem lahan Tanggamus, Gamnokora, dan Talamau memiliki tingkat kerawanan paling tinggi, sementara wilayah dengan sistem lahan Maput, Cipancur, dan Bukit Balang memiliki tingkat kerawanan sedang. Kelas kemiringan lereng digunakan untuk mendetilkan kelas kerawanan longsor pada setiap unit sistem lahan. Hasil pemetaan kerawanan longsor divalidasi dengan peta rawan bencana dari BNPB, menunjukkan persentase kesamaan sebesar 63.51%. Meskipun memiliki akurasi rendah, peta hasil dari data sistem lahan memiliki pola identik pada kelas kerawanan tinggi dan tidak rawan dengan peta referensi. Ini menunjukkan bahwa data sistem lahan dapat digunakan sebagai alternatif dalam pemetaan kerawanan longsor terutama untuk daerah dengan cakupan wilayah yang luas atau pada skala lebih kecil.Abstract. This research aims to optimize the utilization of land system data used to identify areas susceptible to landslide hazards in Majalengka Regency. Landslide occurrence data and land system maps are used as the main data sources, focusing on landslide occurrence patterns in each land system unit. An overlay analysis method between land system maps and landslide occurrence data combined with geomorphological analysis is used to classify the susceptibility levels to landslides. The results indicate that areas with Tanggamus, Gamnokora, and Talamau land systems have the highest susceptibility levels, while areas with Maput, Cipancur, and Bukit Balang land systems have moderate susceptibility levels. Slope classes are used to detail the susceptibility levels to landslides in each land system unit. The landslide susceptibility mapping results are validated with disaster-prone maps from BNPB, showing a similarity percentage of 63.51%. Despite having low accuracy, the mapping results from land system data exhibit identical patterns in high susceptibility and non-susceptibility classes compared to the reference maps. This indicates that land system data can be used as an alternative in landslide susceptibility mapping, especially for areas with extensive coverage or on a smaller scale. Submitted: 2024-05-14 Revisions: 2024-09-19 Accepted: 2024-10-25 Published: 2025-02-17
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.
Analysis of Superior Economic Potential in South Tangerang City with Banten Province Comparator Using Location Quotient, Dynamic Location Quotient, and Shift Share Analysis Methods Khairullah, Muhammad Qabus Abid; Widiastuti, Rastika; Putri, Cindy Adria Ananda; Anggrahita, Hayuning
Jurnal Geografi Lingkungan Tropik (Journal of Geography of Tropical Environments)
Publisher : UI Scholars Hub

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Gross Regional Domestic Product (GRDP) is a key indicator for understanding regional economic structure and dynamics. Differences in sectoral contributions reflect levels of specialization, competitiveness, and growth potential, making comparative and dynamic sectoral analyses essential for regional development planning. This study aims to identify leading, supporting, potential, and lagging economic sectors using Location Quotient (LQ), Dynamic Location Quotient (DLQ), and Shift Share Analysis by comparing the economic performance of South Tangerang City with Banten Province. The analysis is based on GRDP at constant prices by industrial sector for the period 2019-2023. LQ is applied to identify sectoral comparative advantages, DLQ to assess relative growth dynamics, and Shift Share Analysis to evaluate local competitiveness. The results show that South Tangerang City’s economy is predominantly driven by the tertiary sector. Business Services emerge as the only leading sector (LQ > 1 and DLQ > 1), indicating strong structural advantages and favorable growth prospects. Information and Communication, Trade, Construction, Real Estate, Education, and Health Services are classified as base but non-prospective sectors, reflecting a mature development phase. Meanwhile, Public Administration and Electricity and Gas Supply are identified as non-base yet prospective sectors.
Co-Authors Al Kautsar, Azhari Anggrahita, Hayuning Eko Kusratmoko Khairullah, Muhammad Qabus Abid Muhammad Sufwandika Wijaya Putri, Cindy Adria Ananda Tambunan, Mangapul Parlindungan Widiana Putri, Inanditya