Article Per Year (5 Year)
p-Index From 2020 - 2025
0.444
P-Index
This Author published in this journals
All Journal STI Policy and Management Journal Tropical Aquatic and Soil Pollution
Riska Ayu Purnamasari
Department of Soil Science, Faculty of Agriculture, Universitas Gadjah Mada, Indonesia
Chemical Engineering, Chemistry & Bioengineering Chemistry Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
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.
Co-Authors Ernan Rustiadi Kusumawaty, Rini Oryzanti, Parwa Ratna Purwaningsih Setiawan, Marwan Wardah Wardah