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INDONESIA
Indonesian Journal of Geography
Published by Universitas Gadjah Mada
ISSN : 00249521     EISSN : 23549114     DOI : -
Core Subject : Science,
Earth & Planetary Sciences
Indonesian Journal of Geography ISSN 2354-9114 (online), ISSN 0024-9521 (print) is an international journal of Geography published by the Faculty of Geography, Universitas Gadjah Mada in collaboration with The Indonesian Geographers Association. Our scope of publications includes physical geography, human geography, regional planning and development, cartography, remote sensing, and geographic information system. IJG publishes its issues three times a year in April, August, and December.
Arjuna Subject : -
Articles 656 Documents
 62   63   64   65   66 
A Creating Shared Value Approach to Sustainability in Extractive Company Siska Damayanty; Dian Karinawati Imron; Erwinton Simatupang; Dedo Kevin Prayoga; Santoso Tri Raharjo; Risna Resnawaty
Indonesian Journal of Geography Vol 58, No 1 (2026): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijg.107957

Abstract

Transitioning toward a sustainable company is no longer an option but a necessity for the business entity to be agile in responding to sustainability issues. This study examines how an oil and gas company developed a program within the framework of Creating Shared Value (CSV) by bridging the local community and the resources with the company’s value chain. This study was conducted through a case study of the collaborative partnership between PT Pertamina EP Pendopo Field, an oil and gas company, and Sukakarya Village, STL Ulu Terawang Subdistrict, South Sumatra, Indonesia. The results indicate that the company’s initiative lies in developing a CSV prototype program that utilizes areca nuts as a pipe corrosion inhibitor to support the local economy and community empowerment. The company learned to work together with the Kelompok Wanita Tani Melati (Women’s Smallholder Group) and the local community to establish local business clusters. Challenges persist in three key areas: the learning activities related to areca nut extract production, the capacity of local institutions to serve as effective coordinators, and the establishment of cooperative mechanisms between the company and the community. Institutionally, the company has learned to navigate the intersection of sustainability and community-level socioeconomic development by reframing operational challenges concerning local social issues.
Integrating GIS and the MEDALUS Model for Soil Erosion Risk Assessment in Arid Mediterranean Landscapes: A Case Study from the Soubella Sub-Catchment, Hodna, Algeria Djamel KHOUDOUR; Sofiane Bensefia; Zohra BIDI
Indonesian Journal of Geography Vol 58, No 1 (2026): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijg.110431

Abstract

Soil erosion represents a major environmental challenge, particularly in arid and semi-arid regions where natural factors and human activities intensify land degradation. This study evaluates the Soubella sub-catchment's susceptibility to water erosion using the MEDALUS (Mediterranean Desertification and Land Use) model. The assessment is based on four key quality indices Soil Quality Index (SQI), Climate Quality Index (CQI), Vegetation Quality Index (VQI), and Anthropogenic Quality Index (AQI) derived from remote sensing, GIS analysis, and field observations. Spanning 1837.33 km², the study region features diverse topography, with elevations ranging from 376 to 1871 meters and an average slope of 19.02 m/km, indicating moderate terrain. The climate is semi-arid, characterized by high temperatures, limited rainfall, and pronounced spatial and temporal variability. Average annual precipitation at the Soubella dam site is estimated at 289 mm. The findings reveal a distinct spatial classification into three erosion sensitivity levels: non-affected (27.5%), sensitive (16.1%), and highly sensitive (56.4%). The resulting erosion sensitivity map highlights the spatial distribution of vulnerable areas, demonstrating the significant roles of climate, topography, and land use in soil degradation. These insights are crucial for developing targeted and sustainable land management strategies to mitigate erosion risks in the region.Received: 2025-08-15 Revised: 2026-03-05 Accepted: 2026-04-14 Published: 2026-04-20  
Bibliometric Mapping of Impacts and Trends in Erosion Risk Management Research (1992- 2025). Olasunkanmi Olapeju; Mukail Akinde; Olusegun Olaiju; Charlotte Iro-Idoro; Mulkat Yusuff; Babalola Adewara; Vincent Uwala; Eniola Aluko-Jongbo; Tobiloba Ajibade; Elizabeth Ojelabi; Folahan Jibokun; Ibironke Olapeju; Paul Arowolo
Indonesian Journal of Geography Vol 58, No 1 (2026): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijg.112878

Abstract

 Despite the growing body of research on erosion risk management (ERM), a significant gap remains in studies specifically examining ERM through bibliometric analysis. This study bridges this gap by analyzing 81 ERM-related publications retrieved from the Scopus database using bibliometric techniques, VOSviewer, and Microsoft Excel. The analysis reveals that a limited number of prominent authors, affiliations, countries, and funding sources characterize ERM research. The United Kingdom dominates funding of ERM research, with the Environment Agency, Bristol, emerging as the organization with the most ERM-related publications, and India, aggregately, taking the lead as the country that is most associated with ERM research. The triad of Avanzi J.C., Curi N., and Viola M.R. has the most impactful works based on citation counts, with Catena having the reputation of the most cited journal concerning ERM research. A notable increase in ERM publications, post-COVID-19, suggests growing interest in sustainable development and risk assessment techniques like GIS.  Keyword Co-occurrence Analysis (KCA) identified four major research hotspots, which informed the identification of research gaps and future research directions. This study provides a foundation for further exploration of ERM and its potential to drive sustainable development.  
The Development of Inshore Traffic Zone in Sunda Strait Dyan Primana Sobaruddin; Armaidy Armawi; Sri Rum Giyarsih
Indonesian Journal of Geography Vol 58, No 1 (2026): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijg.115071

Abstract

This study aims to delineate spatial conflict zones, assess navigational risk, and formulate geographic information system (GIS)-based design scenarios for a proposed eastern Inshore Traffic Zone (ITZ) in Sunda Strait which is a very important section of Archipelagic Sea Lane I (ALKI I) in Indonesia. International Maritime Organization (IMO) established a western ITZ in 2020, but the eastern sector lacked a systematic nearshore traffic scheme. This is due to the coexistence of competing activities such as fisheries, conservation zones, port access routes, and submarine infrastructure in a limited coastal corridor. Therefore, a spatially integrated method was adopted and combined with Automatic Identification System (AIS)-derived traffic density, longitudinal Vessel Traffic Services (VTS) deviation data, hydrographic maps, and Banten marine spatial planning (RZWP3K) layers in GIS overlay framework. AIS measurements showed that ferry crossings of 2,691–3,168 per month were significantly higher than the longitudinal Traffic Separation Scheme (TSS) flows reported as 365–576 per month and led to frequent crossing encounters in nearshore multi-use areas. The kernel density analysis also signaled that the interactions were concentrated east of TSS corridor specifically in Merak–Cigading waters and Sangiang Island. The two ITZ design possibilities assessed were the complete segregation model and a corridor-oriented layout. The corridor-based ITZ had enhanced spatial compatibility by reducing the overlap between reserve areas and underwater cable routes while augmenting navigational safety. The results showed that GIS-enabled spatial governance could improve traffic management by restructuring movement patterns rather than limiting navigation. This further led to the incorporation of navigational safety goals into maritime spatial planning across intricate archipelagic rivers.
Change in the vegetation cover in En-Nuhud area: Spatio-temporal perspective Ahmed Hamed Elfaig; Amna. M.B. Maryoud; Rihab M. M. Alsmani; Shihabeldeen M. S. Ahmed
Indonesian Journal of Geography Vol 58, No 2 (2026): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijg.102964

Abstract

This study aimed to analyze and identify the dynamics of change in the degradation of vegetation cover at En-Nuhud area, West Kordofan State, Sudan, during the period from 1975-2022. Data were obtained from Landsat Multispectral Scanner (MSS), Enhanced Thematic Mapper Plus (ETM+), and LANDSAT8 OLI for the years 1975, 1985, 1995, 2002, 2012, and 2022. EARDAS and ArcGIS version 10.4 software were used to analyze and process the Normalized Difference Vegetation Index (NDVI) data of the area under study. NDVI, Land Surface Temperature (LST), and Normalized Soil Moisture Index (NSMI) models were adopted to quantify the dynamic changes in degradation of vegetation cover, while Getis-Ord Gi* statistics were calculated to identify hotspot zones. The results showed significant dynamics change in degradation of vegetation cover without a specific rate or trend over space and time. Approximately 29.56%, 44.28%, and 26.16% of the study area suffered from low, moderate, and high degradation, respectively. Furthermore, two distinctive hotspot zones were identified with a confidence level of (P ≥ 0.05). The study has further shown that variability in rainfall coupled with successive and irregular periods of drought had a significant impact on the natural vegetation cover in the area. In conclusion, geo-technologies are identified as an indispensable factor in monitoring and assessing dynamic changes in environmental degradation.Received: 2024-12-23 Revised: 2026-03-05 Accepted: 2026-06-15 Published: 2026-08-05  
Stakeholder Analysis in Greenbelt Planning for Coastal Disaster Mitigation at Yogyakarta International Airport Tri Susmalinda; Dwiko Budi Permadi; Handojo H. Nurjanto
Indonesian Journal of Geography Vol 58, No 2 (2026): In Press
Publisher : Faculty of Geography, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijg.106449

Abstract

The Indonesian government has designated many national strategic projects, including Yogyakarta International Airport (YIA), but the area is prone to coastal disasters, specifically abrasion and tsunamis. Greenbelt planning was proposed as a nature-based solution to mitigate these disasters. This study aimed to disclose the planning processes of YIA and the establishment of coastal forest as a greenbelt area, examine stakeholder participation, and identify the strategies used to implement the policy and plan. A total of 36 key informants were interviewed, and the policy documents were studied to analyze 1) chronology of YIA development planning processes, 2) typology of stakeholders, and 3) social network analysis (SNA) and policy strategies in establishing greenbelt area. The results showed that establishing YIA and Greenbelt required a long-term planning horizon passing through three periods between 2011 and 2020, namely Envision, Acceleration, and Mitigation. Five typologies of stakeholders were identified, including policymakers, planners, facilitators, implementers, farmer groups, and academicians. SNA showed that the forestry agency played a significant role in maintaining the communication and networks among the other stakeholders to establish greenbelt. This forestry agency used incentives, such as providing seedlings, technical guidance, and planting and maintenance costs for farmer groups. Government agencies (provincial, district, and village level) generally used a regulatory method (coercion) and dominant information to influence shrimp-pond farmers to leave the pond areas for greenbelt establishment. This study showed the importance of smart coordination in greenbelt planning using multiple strategies when complex problems arise. Received:2025-05-03Revised: 2026-03-05 Accepted: 2026-06-15  Published: 2026-08-05  
Spatial Determinants of Childhood Obesity: Analysing Environmental and Socioeconomic Influences Jehan Sabeeh Mosleh
Indonesian Journal of Geography Vol 58, No 2 (2026): In Press
Publisher : Faculty of Geography, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijg.110465

Abstract

One of the critical public health concerns worldwide is childhood obesity, which affects both developed and developing countries. Addressing this issue requires understanding its scope and analysing its causes and contributing factors. Recent studies highlight how obesity rates vary globally, with growing attention paid to the role of local socioeconomic and environmental factors. Thus, this work integrates these updated findings to propose hypotheses explaining Sheffield's observed patterns, aligning local data with broader public health insights. This study investigates the spatial distribution and prevalence of childhood obesity among Year 6 students in Sheffield, UK. Utilizing a high-granularity baseline from the 2016/2017 National Child Measurement Programme (NCMP) alongside the Income Deprivation Affecting Children Index (IDACI), the analysis examines the spatial overlap between fast-food outlet density, green space accessibility, and income deprivation. While longitudinal data (2016–2024) confirms a persistent prevalence gap between Sheffield and national averages, spatial analysis reveals a significant "East-West" gradient. The analysis reveals an average obesity prevalence of 19.21% across the city wards, with rates ranging from 7.5% to 28.2%, with statistically significant spatial autocorrelation (Global Moran’s I > 0; p < 0.05) identifying distinct obesity clusters in eastern and central wards. Findings suggest that socioeconomic deprivation acts as an effect modifier; specifically, the protective benefits of green space appear negated in high-deprivation zones characterized by "food swamp" environments. The conclusions highlight the need for targeted interventions —such as Hot Food Takeaway (HFT) exclusion zones within the Sheffield Local Plan— to address these entrenched spatial health disparities and promote equitable outcomes.Received: 2025-08-17 Revised: 2025-12-11 Accepted: 2026-06-12 Published: 2026-07-28
A Data-Efficient Rice Yield Classification Framework Combining Hybrid PCA-RFE and Regularized Random Forest Yagus Wijayanto; Rika Nurjannah; Maya Wenlow Saragih; Ika Purnamasari; Tri Wahyu Saputra; Suci Ristiyana; Ummi Sholikhah; Rachmat Abdul Gani
Indonesian Journal of Geography Vol 58, No 2 (2026): In Press
Publisher : Faculty of Geography, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijg.111239

Abstract

Accurate rice yield prediction by remote sensing data and machine learning is still a big challenge in limited resources of field survey where the sample size is often very small. This study tackles the core challenge of small sample size (n=39) in rice yield classification by proposing a hybrid feature engineering framework that combines Principal Component Analysis (PCA) and Recursive Feature Elimination (RFE) in a regularized Random Forest (RF) classifier. The methodology is based on 30 spectral features from multi-temporal Sentinel-2A imagery (15 spectral bands i.e. Bands 2, 3, 4, 5 and 8 for three acquisition dates and 15 vegetation indices). PCA revealed three principal components that explained approximately 90% of the total variance and RFE selected the five most discriminative spectral bands (SAMPLE_14, SAMPLE_15, SAMPLE_17, SAMPLE_23 and SAMPLE_26). These were fused in a compact eight-dimensional hybrid feature space. Model evaluation was conducted using repeated stratified cross-validation (5-fold x 10 repeats) and an independent test set (holdout 30%). The average cross-validation accuracy of the hybrid model was 83.36%, ROC-AUC 0.9304, independent test accuracy 91.67% and Cohen's Kappa 0.8333. There was no over-fitting of the training-validation gap to 0.10 in the learning curve. The optimal classification threshold was identified as 0.5373 in the Youden Index optimization. The RFE-selected spectral bands contributed the largest share (76%) in the feature importance analysis, and the PCA components provided a complementary 24%, confirming the synergistic value of unsupervised extraction and supervised selection. However, spatial uncertainty mapping revealed limitations to the overall extrapolation, with near-maximum values (0.999) in unsampled areas, emphasizing the need for targeted field verification in high-uncertainty zones. The study provides a replicable methodological blueprint for crop yield classification under very limited data conditions and provides practical guidance for agricultural monitoring in developing countries with logistical and financial constraints.Received: 2025-09-15 Revised: 2026-06-26 Accepted: 2026-07-28 Published: 2026-08-05 
Geographical and Seasonal Fluctuations in Temperature and Rainfall Across the Kegalle District, Sri Lanka Piratheeparajah Nagamuthu; Roshani Vijayakumar
Indonesian Journal of Geography Vol 58, No 2 (2026): In Press
Publisher : Faculty of Geography, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijg.112152

Abstract

Currently, precipitation and temperature stand as the foremost indicators of climate change, exerting a profound and far-reaching influence on the global environment. This scholarly inquiry endeavors to illuminate the spatial and temporal dynamics of these climatic variables—fundamental markers of seasonal variation in the Kegalle District—spanning 41 years from 1981 to 2024.  These datasets were subjected to rigorous trend analysis utilising Minitab, employing the Mann-Kendall test alongside Sen's Slope Estimator to detect and interpret temporal patterns. Among the ten selected localities, Yatiyanthota exhibits the most pronounced temperature fluctuations, with an average of 26.5°C and a minimum of 19.25°C, where temperatures reach 34.8°C. Notably, this region exhibits a decline in maximum temperatures alongside an increase in minimum temperatures. Conversely, Aranayaka maintains a relatively moderate mean temperature of 18.9°C. Rainfall observations reveal that Rambukkana experiences the highest precipitation, with an increase of 1,826 millimeters, whereas Deranyagala records the lowest.  On a monthly scale, October and November receive the greatest rainfall, whereas April and March are characterised by minimal precipitation coupled with elevated temperatures. Trend analyses identify Aranayake as the locale with the lowest averages of both temperature and rainfall.Received: 2025-10-16 Revised: 2026-04-29 Accepted: 2026-07-13 Published: 2026-08-05
Integrating Machine Learning and Deep Learning to Predict Settlement Land Use Change and Carrying Capacity: A Case Study of Metro City, Indonesia Anggun Tridawati; Fajriyanto Fajriyanto; Armijon Armijon; Tika Christy N; Bella Rahmalia; Soni Darmawan
Indonesian Journal of Geography Vol 58, No 2 (2026): In Press
Publisher : Faculty of Geography, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijg.112398

Abstract

Rapid population growth and urban expansion in Metro City, Lampung Province, Indonesia, have intensified pressure on land resources and environmental sustainability. Therefore, this study aimed to integrate machine learning (Support Vector Machine, SVM) and deep learning (Cellular Automata–Artificial Neural Network, CA–ANN) to analyze as well as predict settlement land-use changes and assess land carrying capacity through 2038. SPOT satellite imagery from 2013, 2018, and 2023 was used for land cover classification. The results showed that settlement areas expanded from 1,087.16 ha in 2013 to 2,700.23 ha in 2023 and are projected to reach 4,336.22 ha by 2038, primarily driven by population growth and improved accessibility. The land carrying-capacity index ranged from 3.15 to 11.09, indicating that all districts remain above the minimum threshold (DDPm > 1), suggesting sufficient land availability to support projected settlement demand through 2038. Overall, the integration of SVM and CA–ANN proved effective for modeling complex urban dynamics and predicting future settlement changes. In conclusion, the results provide a scientific foundation for policymakers and urban planners to design data-driven and sustainable spatial development strategies in rapidly growing secondary cities.Received: 2025-10-23 Revised: 2026-05-04 Accepted: 2026-06-09 Published: 2026-08-05 

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