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Forum Geografi
Published by Universitas Muhammadiyah Surakarta
ISSN : 08520682     EISSN : 24603945     DOI : -
Core Subject : Science,
Earth & Planetary Sciences
Aim Forum Geografi is an open-access, peer-reviewed journal dedicated to advancing the field of geography by publishing original scientific articles on spatial issues. The journal prioritizes studies that employ rigorous spatial analysis and geospatial technologies—such as GIS and remote sensing—to deepen theoretical and empirical understanding of spatial patterns, processes, and interactions in both physical and human geography. Focus The primary focus of Forum Geografi is on studies that apply Geographic Information Systems (GIS) and/or remote sensing for spatial and regional analysis of physical and human geographic phenomena. Scope - Human and environment interaction - Geomorphology: process and modelling - River basin: process and modelling - GIS and/or Remote sensing-based disaster-related study - Urban, rural, and regional study
Arjuna Subject : Ilmu Bumi dan Planet (semua kategori) - Geologi
Articles 97 Documents
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Flood Risk Analysis Using Spatial Synthetic Population in the Upper Bengawan Solo Watershed, Indonesia Muhammad Musiyam; Jumadi Jumadi; Vidya Nahdhiyatul Fikriyah; Heni Masruroh; Ema Dwi Septiyani; Choirul Amin; Hamim Zaky Hadibasyir; Farha Sattar; Muhammad Nawaz
Forum Geografi Vol. 39 No. 3 (2025): December 2025
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v39i3.13611

Abstract

This study develops a spatial synthetic population (SSP)-based computational model to produce realis-tic, high-resolution flood-risk maps for the Upper Bengawan Solo Watershed. It combines Global Hu-man Settlement (spatial distribution) with local population statistics (attributes). The SSP is created for flood risk mapping in the Upper Bengawan Solo Watershed (BSH) using a 100 m grid from the Global Human Settlement Layer (GHSL) GHS-POP R2023A. Synthetic individuals are strategically placed around the pixel centre (radius ≤ 100 m), and each is assigned demographic attributes (age, gender, ed-ucation, occupation) validated against official county-level data. Social vulnerability is calculated through weighted aggregation (AHP) across four attributes; individual scores are combined with flood hazard intensity at each location to produce a risk index for each person. Validation shows that (i) the SSP aligns closely with reference statistics: gender and age are nearly identical (MAE ≈ 0.01–0.02%), with slight deviations in occupation (MAE 6.52%) and education (MAE 4.89%), (ii) the overall suita-bility of the SSP compared to GHS counts at pixel samples, and (iii) location plausibility testing using ESRI Sentinel‑2 Land Cover (10 m). Results indicate that (i) the SSP aligns well for gender, moderately for education and occupation, but shows significant misalignment in age, (ii) 91.96% of SSP points are in built-up land, suggesting high spatial accuracy. Medium- to high-risk patterns are mainly along the main river corridors and peri-urban areas, while rural non-built zones are mostly low- to medium-risk. These findings suggest that this methodology is scalable, reproducible, and suitable for data limited regions, enabling the production of detail risk maps that can guide mitigation and preparedness efforts.
Characteristics of Precipitable Water Vapor of Mesoscale Convective System During Heavy Rainfall over Greater Jakarta, Indonesia, March 3-4 2025 Prasetyo Umar Firdianto; Bagus Satrio Wicaksono; Asep Adang Supriyadi; Nanang Yulian; Bangun Muljo Sukojo; Danang Eko Nuryanto
Forum Geografi Vol. 40 No. 1 (2026): April 2026
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.13886

Abstract

Across the Indonesian Maritime Continent, pronounced convective activity frequently initiates cloud systems that can further organize and evolve into mesoscale convective system (MCS). This triggers extreme weather and flash flooding; for example, on March 3-4, 2025 in Greater Jakarta. This study investigates the impact of such systems on precipitable water vapor (PWV) using GNSS observations, the ERA5 reanalysis model, and Himawari satellite data. The datasets include rainfall observations, GNSS RINEX data, ERA5 reanalysis, GPM satellite precipitation, and brightness temperature from Himawari-8 channel 8. Analysis was conducted on variability, timeseries, scatter , boxplots, bias, MAE, RMSE standard deviation, correlation, and coefficients of determination. The results indicate that PWV exhibits marked fluctuations that align with the MCS period. The distance of observation and MCS track have a significant influence on modulating PWV, whereas PWV has a weak correlation with MCS intensity. Consistent fluctuations were detected in both the GNSS and ERA5 derived PWV, although GNSS demonstrated higher sensitivity in describing PWV fluctuation compared to ERA5. Variation in brightness in the upper-level moisture demonstrate consistent with PWV, athough the correlation remains weak. MCSs to enhanced rainfall, which can trigger extreme weather conditions and flash flooding.
Land Suitability Evaluation for Citrus Cultivation using GIS and AHP for Different Land Units in Indonesia Basuki Basuki; Zaky Fahrian Rizaldi; Vega Kartika Sari; Sukron Romadhona
Forum Geografi Vol. 40 No. 1 (2026): April 2026
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.14319

Abstract

The objective of this research is to evaluate the suitability of land for horticultural crops, particularly citrus cultivation, in an effort to increase productivity and support food security in Indonesia. The FAO land evaluation workflow through the Analytic Hierarchy Process (AHP) method was employed, together with the geographic information system (GIS), with several stages of activities such as preparation, survey and data analysis. In the initial stage, a land unit (LU) was formed to facilitate survey activities, data collection and data analysis. The data are analyzed for actual land suitability, followed by AHP analysis to determine relative priorities and potential land suitability. Our study shows that AHP technology is very effective in determining priority weights, as indicated by a consistency ratio (CR) value of <0.1. This condition implies a high and strong dependence on the environment. Environmental parameters that influence the evaluation and have a significant impact on citrus land suitability include rainfall (16%), drainage (15%), soil texture (12%) and erosion risk (4%). The results of the AHP analysis show that 18.57% of the study area is highly suitable (S1) for citrus plants; 65.28% is moderately suitable (S2); and 16.15% is slightly suitable (S3). The principal constraints of the soils are low nutrient content, poor rooting condition, and erosion risk. According to the study, management techniques such as the incorporation of organic matter and inorganic fertilizers, and the addition of mounding soil for plant systems, such as surface or subsurface drains, are required for long-term productivity.
Climate Change and Flooding: Bibliometric Analysis to Identify Future Research Davronjon Allayorov; Kudrat Rakhimov; Uchqun Umarov; Dinislam Atakulov; Dilbar Allayorova; Samandar Shaymardonov
Forum Geografi Vol. 40 No. 1 (2026): April 2026
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.14508

Abstract

Among the various hydroclimatic phenomena, floods occupy a special place due to their environmental and socio-economic impact. However, identifying the main focus of research related to climate change and floods requires the examination of a large number of publications. This article presents a bibliometric analysis of publications on climate change and floods from the Web of Science database during the period 2015 to 2024. The analysis indicates that climate change-induced flood research is a rapidly expanding and increasingly popular field. The majority of publications (94%) were scientific articles, and in the 5 years up to 2024 there has been an improvement in their quality. Much of the research was conducted in China, the US, and EU. The Chinese Academy of Sciences is a leader in this field, and journals such as Science of the Total Environment, Water, and the Journal of Hydrology are active in disseminating research results. Bibliometric analysis using VOSviewer and Bibliometrix found that in the climate change context, the major institutions are studying precipitation changes and water management in catchments. Flood susceptibility and streamflow forecasting are the central topics that need to be studied in-depth in order to develop highly accurate early warning systems. During the process, physically-based hydrological modelling must also be incorporated using advanced soft computing techniques, particularly machine learning, artificial neural networks, and geospatial tools such as geographic information systems and remote sensing.
Spatial Relationships Between Flash Drought and Rice Production in a Tropical River Basin Using Geographically Weighted Regression Widjonarko Widjonarko; Hartuti Purnaweni; Maryono Maryono; Imam Buchori; Anang Wahyu Sejati; Alexander Zipf
Forum Geografi Vol. 40 No. 3 (2026): December 2026
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.14598

Abstract

Flash droughts have become a significant hydroclimatic hazard threatening agricultural production amid increasing climate variability. However, studies examining the spatial relationship between flash drought indicators and rice production in the humid tropics are limited. This research aims to assess the impacts of flash droughts on rice production in Bengawan Solo River Basin using a GIS-based geographically weighted regression (GWR) method. Soil moisture (SM), land surface temperature (LST) and rainfall (RF) were employed as independent variables and rice production (RP) as the dependent variable. The results show that flash droughts significantly reduce paddy yield, with all the independent variables having a significant influence (R² = 71.43%). Residual Moran’s I analysis indicated no significant spatial autocorrelation (z-score = -0.5; p-value = 0.6), confirming the robustness of the model. Among the three independent variables, SM and LST were the most statistically significant (probability t value < 0.05). Based on a simulation using the average local GWR coefficient, a 1% decrease in SM combined with a 1% increase in LST potentially reduced rice production by up to 9.62%.  These findings demonstrate a strong spatial relationship between flash drought indicators and declining rice production. Consequently, the importance of strengthening mitigation and adaptation strategies to reduce potential future losses in rice production is emphasised.
GeoAI-Based Prediction of Yellowfin Tuna (Thunnus albacares) Potential Fishing Zones in the Western Sumatra Waters, Indonesia Amir Yarkhasy Yuliardi; Muhammad Hanif; Septy Heltria; Diah Ayu Rahmalia; Gandhi Napitupulu
Forum Geografi Vol. 41 No. 1 (2027): April 2027
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.15234

Abstract

The western waters of Sumatra in the eastern Indian Ocean are highly productive fishing grounds for yellowfin tuna (Thunnus albacares). However, the dynamic oceanographic conditions of these waters pose challenges for reliable fisheries prediction. Therefore, this study aimed to identify key environmental drivers and predict Potential Fishing Zones (PFZs) using GeoArtificial Intelligence (GeoAI)-based machine learning (ML) framework integrating Guided Regularized Random Forest (GRRF) and Random Forest (RF). The predictive models were developed using multi-source oceanographic variables as predictors, including sea surface temperature (SST), chlorophyll-a (Chl-a), salinity, current velocity, and net primary productivity (NPP). The results of correlation analysis showed that there was a strong relationship between Chl-a and NPP (r = 0.87), indicating the central role of primary productivity in tuna habitat dynamics. Both models achieved high predictive accuracy, with GRRF slightly outperforming RF by reducing variable redundancy and improving interpretability. Tuna occurrence was strongly associated with moderate SST (29.2–29.8°C), high NPP (>350 mg C m⁻² day⁻¹), and zones influenced by the South Java Coastal Current (SJCC) and the Indonesian Throughflow (ITF). Spatially, PFZs were concentrated along the Mentawai slope and adjacent offshore waters, particularly during monsoon transition periods. These results showed the effectiveness of GeoAI-based methods for predicting PFZs and supported sustainable tuna fisheries management. Moreover, future studies should incorporate interannual climate variability (ENSO, IOD) and advanced deep learning frameworks to enhance spatiotemporal prediction.
High-Resolution Bathymetry of the Southern Pantar Strait Reveals the Deep Cold-Water Source of Extreme Upwelling off Alor Kecil, Indonesia Anindya Wirasatriya; Gentio Harsono; Dwi Haryanti; R. Dwi Susanto; Lilik Maslukah; Yusuf Jati Wijaya; Ni Kadek Dita Cahyani; Rizki Taqwa Putranto; Riandi Teguh Widiyandono; Faisal Hamzah; Iis Triyulianti; Muhammad Helmi; Alexander Yosep Elake; Gede Iwan Setiabudi; Deirus Rizki Khair; Mohan Syafaat; Danar Judas Pratama; Yohanes Theo Medika; Darminto Darminto; Agung Setyo Sasongko; Azis Rifai; Dwiyoga Nugroho; Jahved Ferianto Maro
Forum Geografi Vol. 40 No. 3 (2026): December 2026
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.15332

Abstract

An extreme upwelling event (EUE) off Alor Kecil (central Pantar Strait, Indonesia) can cause sea-surface temperature (SST) to drop by >10 °C within hours, indicating rising cold water from the deep basin. The EUE occurs along the Mulut Kumbang Strait, a narrow channel 300 m wide and 900 m long. Understanding the water-mass origin of the EUE may provide insights into the mechanism of EUE generation. Prior eDNA analyses suggested a deep-ocean source (Savu Sea Basin) based on the detection of bathypelagic fish genetic materials at the Mulut Kumbang Strait during the EUE, which indicates that the water-mass origin of the EUE may come from a depth of more than 1,000 m. To confirm the source of the cold-water mass, we present a multibeam echosounder (MBES) bathymetric survey to observe the detailed bottom morphology of the Pantar Strait. We also provide Conductivity Temperature Depth (CTD) data from five stations in the Pantar Strait, which measure the vertical profile of temperature. We identified five basins in the southern Pantar Strait that are likely the sources of the cold-water mass originating in the Mulut Kumbang Strait. The first basin is situated south of the Mulut Kumbang Strait and has a depth of approximately 150 m. The second, third, and fourth basins are aligned further south, with depths of ~350, ~400, and ~600 m, respectively. The deepest and largest basin is located at the southernmost point of the Pantar Strait, adjacent to the Savu Sea, and reaches a maximum depth of 1,060 m. The area of the basin that exceeds 1,000 m in depth covers 4.75 km2. CTD data confirm that temperatures below 10 °C are found at depths greater than 400 m. We infer that the largest and deepest basin at the southern end of the Pantar Strait is a plausible source reservoir for the cold-water mass during the EUE, which is potentially connected to the Mulut Kumbang Strait via a tapered channel.
Assessing Landslide Susceptibility in Batu City, Indonesia: A Machine Learning Approach Using Google Earth Engine Muhardi Muhardi; Adi Susilo; Eko Andi Suryo; Yoga Satria Putra; Muwardi Sutasoma; Rahmat Faizal; Nur Aini Gama Lestari; Rony Prianto Nugraha; Andy Anderson Bery; Muhammad Fathur Rouf Hasan
Forum Geografi Vol. 40 No. 2 (2026): August 2026
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.15658

Abstract

This study aims to map landslide susceptibility in Batu City, East Java Province, Indonesia, using machine learning on the Google Earth Engine platform. Five algorithms were used: random forest (RF), classification and regression trees, support vector machine, gradient tree boosting, and k-nearest neighbors. Landslide susceptibility data were collected from 276 sample points, comprising 138 landslides and 138 nonlandslides. The data were divided into two parts: 70% for training and 30% for testing. The conditioning factors initially considered consisted of 13 variables. Pearson correlation matrix analysis indicated that annual rainfall should be excluded to avoid multicollinearity, resulting in 12 predictors used for mapping: elevation, slope, aspect, landforms, distance from rivers, topographic wetness index, soil types, land use/land cover, normalized difference vegetation index, distance from roads, geological formations, and distance from lineaments. Model performance was evaluated using six metrics: accuracy, precision, recall (sensitivity), F1-score, kappa coefficient, and area under the receiver operating characteristic curve. Model validation results indicated that the RF algorithm was the best model. The RF-based landslide susceptibility map classified the area into five classes: very low class covering an area of 60.70 km2 (30.49%), low class covering an area of 29.47 km2 (14.80%), medium class covering an area of 16.21 km2 (8.14%), high class covering an area of 22.56 km2 (11.33%), and very high class covering an area of 70.16 km2 (35.24%). Variable importance analysis showed that slope is the most influential factor, with a mean decrease in impurity of 43.77 (15.36%), whereas soil types had the least contribution. This study successfully mapped landslide susceptibility using a machine learning approach, enabling direct support for disaster mitigation planning and risk-based land use in Batu City.
Sustainable Tourism Development in Labuan Bajo, Manggarai Barat, Indonesia: Integration of Multi-Hazard Risk Analysis into Spatial Planning Osmar Shalih; Muhammad Baiquni; Sudaryatno
Forum Geografi Vol. 41 No. 1 (2027): April 2027
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.15757

Abstract

The rapid growth of ecotourism in island regions such as Labuan Bajo, Manggarai Barat, Indonesia, has not adequately considered the integration of comprehensive multi-hazard risk assessments into spatial planning. The area is becoming more vulnerable to a mix of geophysical, hydrological and climatological hazards as it is designated a "Super Priority" tourism destination in the country. However, current planning practices do not fully account for these hazards. This study examines how multi-hazard risk is incorporated into the Regional Spatial Plan of Labuan Bajo, Manggarai Barat, through a mixed-methods approach combining GIS-based multi-hazard analysis using spatial overlay techniques, together with qualitative insights from key stakeholders. A composite multi-hazard risk index was overlaid with land-use zoning, activity centres and transportation networks to evaluate spatial suitability and infrastructure exposure. The analysis indicates that planned land use does not align with the current risk levels, as high-risk areas have been designated for residential zones, tourism areas and major transportation corridors, demonstrating that spatial suitability varies according to multi-hazard risk levels in the study area. On the other hand, conservation areas are more suitable for low-risk environments. The results indicate that high-risk island tourism areas require more effective spatial planning based on risk information in order to remain resilient and sustainable in the long term.
Urbanisation Dynamics and Socio-Spatial Transformation: Evidence from Samarkand, Uzbekistan Lutfullo Ibragimov; Aigul Sergeyeva; Gulmira Barotova; Mirlan Dyldaev; Normurod Latipov; Bekzod Мusayev
Forum Geografi Vol. 40 No. 3 (2026): December 2026
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.15827

Abstract

Urbanisation in post-Soviet Central Asia has accelerated significantly over recent decades, reshaping demographic structures, land use patterns and socio-economic development trajectories across the region. Considerable attention has been paid to the capital city of Tashkent, whereas the urbanisation dynamics of secondary cities and their surrounding regions remain insufficiently explored in the academic literature. This study addresses that gap by examining urbanisation processes in the Samarkand region of Uzbekistan during the period 2010–2025. Urbanisation trends are analysed through an assessment of the relationships between urban population growth, demographic changes and the socio-economic development of the region. The study is based on official statistical data. The methodological approach includes correlation analysis, together with cartographic analysis and GIS visualisation to identify spatial differences in the level of urbanisation. The results indicate that urban population growth in the Samarkand region is driven primarily not by rural-to-urban migration, but by internal demographic factors such as high fertility rates and a sustained natural population increase (r = +0.967 between urban population and births). Urbanisation is closely associated with growth in industrial output (r = 0.91); increased investment in fixed capital (r = 0.88);  and intensified construction activity (r = 0.89), together with rising employment and the expansion of the service sector. At the same time, a reduction in agricultural land is observed, particularly in suburban areas, as reflected in the inverse correlation between urbanisation and agricultural land area (r = −0.69). The findings demonstrate that urbanisation in the region is following a gradual and internally-driven trajectory. The study highlights the need for coordinated spatial planning and balanced land-use policies to ensure sustainable socio-economic development in the Samarkand region.

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