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All Journal STI Policy and Management Journal Tropical Aquatic and Soil Pollution Buitenzorg: Journal of Tropical Science
Riska Ayu Purnamasari
Department of Soil Science, Faculty of Agriculture, Universitas Gadjah Mada, Indonesia
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Earth & Planetary Sciences Engineering Environmental Science Health Professions

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Analysis of Obstacles For Mangosteen Agro-Industry Revitalization In Karacak Agropolitan Area, Indonesia: An Interpretive Structural Modeling Approach Oryzanti, Parwa; Wardah, Wardah; Setiawan, Marwan; Purnamasari, Riska Ayu; Kusumawaty, Rini; Purwaningsih, Ratna; Rustiadi, Ernan
STI Policy and Management Journal Vol 9, No 1 (2024): STI Policy and Management
Publisher : National Research and Innovation Agency, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/STIPM.2024.381

Abstract

This study aims to identify and propose solutions to the obstacles faced in the study of Karacak Agropolitan Revitalization based on Mangosteen agroindustry in Bogor Regency as outlined in a structural model. The revitalization of agro-industry-based agropolitan areas is studied through science, technology, and innovation which are then formulated and analyzed with the Interpretive Structural Modeling Method. Primary data were collected through expert-based surveys and questionnaires from seven relevant and representative government agencies to formulate policy studies. This research resulted in a study of 9 sub-elements of constraints and found 1 key sub-element, arrange hierarchically based on its importance. At the most critical level, we identified the government's political will towards agro-industrial development incentives and disincentive programs in agropolitan areas. This study recommends the government start an integrated agropolitan area revitalization program by utilizing local biological resources. The systems model approach will facilitate sustainable development at the village level, promoting inclusive economic growth and resilience. Keywords: Agropolitan, Barriers, Interpretive Structure Modeling, Mangosteen Agroindustry.
Land Degradation Detection in Urban Areas Using Spatial Modelling and Semi-Automatic Classification of Satellite Imagery Data Purnamasari, Riska Ayu; Setiawan, Marwan; Wardah, Wardah
Tropical Aquatic and Soil Pollution Volume 5 - Issue 2 - 2025
Publisher : Tecno Scientifica Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53623/tasp.v5i2.775

Abstract

Urban land degradation poses a growing challenge in rapidly developing countries like Indonesia, where population growth and limited space drive uncontrolled land cover changes. This study aims to detect land degradation in urban areas through spatial modelling and semi-automatic classification of multi-temporal remote sensing imagery. Landsat-5 Thematic Mapper (TM) image from year 2011 and Landsat-9 Operational Land Imager collection 2 (OLI-2) image from year 2023 data were acquired from the The United States Geological Survey (USGS). Image pre-processing included band stacking, subsetting, and enhancement to improve visual interpretation. Semi-automatic supervised classification was applied to map seven land cover classes: agricultural dry land, rice field, forest, plantation, non-agricultural land, water body, and settlement. Training data and validation were supported by Google Earth Pro, official sources, and field surveys using random sampling. Change detection analysis revealed a 1664.65 ha increase in industrial areas, accompanied by significant reductions in rice fields (−1726.92 ha) and dry farmland (−1644.57 ha). The classification accuracy reached 80.24% and 75.11%, with kappa coefficients of 0.76 and 0.65, respectively. Results indicate that urban expansion is a key driver of land degradation, particularly through the loss of productive agricultural land. This research demonstrates the effectiveness of remote sensing-based spatial modelling and classification techniques for monitoring urban land degradation and informing sustainable land use planning.
Evaluasi Faktor-Faktor Pendorong di Balik Transisi Lahan Perkotaan di Wilayah Pesisir: Integrasi Pendekatan Geospasial dan Pengetahuan Lokal Riska Ayu Purnamasari
Buitenzorg: Journal of Tropical Science Vol 3 No 1 (2026): Buitenzorg: Journal of Tropical Science
Publisher : Innovation Centre for Tropical Sciences

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70158/buitenzorg.v3i1.46

Abstract

Agricultural land transition in rapidly urbanizing coastal regions poses significant challenges for sustainable land use planning and long-term food security. This study examines the driving forces behind agricultural land conversion in Cilegon City, Banten Province, Indonesia as one of Southeast Asia's most industrialized coastal cities by integrating Remote Sensing (RS), Geographic Information Systems (GIS), and the Analytical Hierarchy Process (AHP) with structured local knowledge elicitation. Land cover classification was performed using Random Forest machine learning applied to multi-temporal Landsat imagery (2011 and 2023), revealing substantial encroachment of non-agricultural land uses. Through pairwise comparison interviews with six domain experts, AHP weighting assigned the highest influence to rainfall (18%), soil quality (15%), and road accessibility (14%) as transition drivers. The resulting transitional suitability map, validated against observed land cover change, achieved an overall accuracy of 88.70% and a Kappa coefficient of 0.86, demonstrating the model's strong predictive capacity. The findings underscore that environmental, infrastructural, and socio-economic factors collectively govern land conversion dynamics. This study contributes a replicable, participatory spatial framework that bridges objective geospatial data with community-embedded knowledge, supporting more inclusive, evidence-based urban planning and agricultural land management in fast-growing coastal cities.   Keywords: analytical hierarchy process, coastal city, land use change, local knowledge, remote sensing.
Co-Authors Ernan Rustiadi Kusumawaty, Rini Oryzanti, Parwa Ratna Purwaningsih Setiawan, Marwan Wardah Wardah