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All Journal International Journal of Public Health Science (IJPHS) Indonesian Journal of Geography Geo Media: Majalah Ilmiah dan Informasi Kegeografian Jurnal Pembangunan Wilayah dan Kota Media Komunikasi Geografi Jurnal Geografi : Media Informasi Pengembangan dan Profesi Kegeografian Jurnal Teknosains Geoplanning : Journal of Geomatics and Planning Majalah Geografi Indonesia JTSL (Jurnal Tanah dan Sumberdaya Lahan) Jurnal Ketahanan Nasional JURNAL AGROTEKNOLOGI Forum Geografi JURNAL PENDIDIKAN KEPERAWATAN INDONESIA GEA, Jurnal Pendidikan Geografi Jurnal Fisika FLUX Journal of Applied Geospatial Information Jurnal Kesehatan Vokasional Jurnal Geografi Forest and Society International Journal of Remote Sensing and Earth Sciences (IJReSES) JAGAT (Jurnal Geografi Aplikasi dan Teknologi) Socius (Jurnal Pendidikan dan Pembelajaran Ilmu Pengetahuan Sosial) (Edisi Elektronik) Jurnal Geosains dan Remote Sensing (JGRS) geoedusains: Jurnal Pendidikan Geografi GEOGRAPHIA: Jurnal Pendidikan dan Penelitian Geografi JKKI : Jurnal Kedokteran dan Kesehatan Indonesia Proceeding ISETH (International Summit on Science, Technology, and Humanity) Jurnal Manusia dan Lingkungan Aerospace Engineering IJES : Indonesian Journal of Environmental Sustainability. The International Journal of Remote Sensing and Earth Sciences (IJReSES)
Prima Widayani
Magister Penginderaan Jauh, Fakultas Geografi, Universitas Gadjah Mada
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Earth & Planetary Sciences Education Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

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Land-Cover Change Detection in Batur Catchment Area Using Remote Sensing Febrianti, Ni Kadek Oki; Danoedoro, Projo; Widayani, Prima
JURNAL GEOGRAFI Vol. 15 No. 1 (2023): JURNAL GEOGRAFI
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/jg.v15i1.32670

Abstract

Land cover information is an essential aspect in the planning and management of earth modeling and understanding. Land cover changes impact the physical and social environment, such as hydrological conditions and ecological systems. This study aimed to identify spatial differences in the land cover of the Batur catchment area from 2015-2021 by using a remote sensing approach to describe the existing land-cover site and to detect its changes. The methods used in this study are a combination of the vegetation index and a supervised classification maximum likelihood algorithm with Landsat 8 OLI/TIRS in 2015 and 2021. Furthermore, the Change Detection Feature, identified from two image periods in 2015-2021 and processed, is used to detect changes in land cover. The accuracy assessment utilized QuickBird imagery recorded in 2015; field survey data were taken in 2021. The results showed that between 2015 to 2021, built-up area, bare land, shrubs, and lake have increased by 102,66% (306,01 ha), 27,95% (452,25 ha), 15,20% (215,72 ha) and 4,05 % (62,73 ha) while dryland forest and dry-dry-field have decreased by -25,84% (-606,29 ha) and -14.59% (-430,42 ha), respectively. The overall accuracy of the multispectral classification results in 2015 and 2021 was 82,63% and 89,57%.Keywords: Land-Cover Change; Batur; Catchment Area; Remote Sensing 
MODIS Satellite Imagery for Monitoring Carbon Sequestration Potential and Its Drivers in Jambi Province, Indonesia Widayani, Prima; Arrafi, Muhammad
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.v17i1.62343

Abstract

Jambi Province is a province in Indonesia whose land use is dominated by forests and plantations. Threats to land conversion and forest fires in the region have reduced vegetation and will threaten carbon absorption in the future. This study aims to map and assess the potential for carbon absorption and triggering factors by evaluating the spatiotemporal Net Primary Productivity (NPP) pattern to estimate Jambi Province's carbon absorption. This study uses remote sensing data to obtain NPP values ​​and several variables that will be assessed for their influence on NPP. MODIS satellite imagery is used to obtain NPP data, forest cover, Normalized Data Vegetation Index (NDVI) and Land Surface Temperature (LST). Shuttle Radar Topography Map (SRTM) imagery obtains topography and slope data. Population data in the form of the Human Development Index, total population and population in urban areas were obtained from the Central Statistics Agency of Jambi Province. The average NPP value 2003 in Jambi Province was 0.911 kgC/m/year, then the average NPP decreased to 0.754 kgC/m/year in 2023. Based on statistical analysis, there is a correlation between NPP and NDVI, slope, and topography.
RESIDENTIAL CLASSIFICATION USING GEOBIA IN PART OF JAKARTA SUBURBAN AREA Akmal Hafiudzan; Prima Widayani; Nurwita Mustika Sari
International Journal of Remote Sensing and Earth Sciences Vol. 20 No. 2 (2023)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2023.v20.a3862

Abstract

The increasing of urban population followed by socioeconomic problems leads to emerging various number of researchs in urban area, especially in Jakarta Metropolitan Area. One of them are escalated tension-conflict due to rise of newly Gated Communities residential that sprawl across local residents (Kampung Kota). There is urgency to map all 3 types of residential (Kampung Kota, Perumnas, Cluster) through satellite imagery on a wide-scale. This study uses WorldView-2 imagery data recorded for 2020. The method used is an object-based method, namely GEOBIA using the eCognition Developer 64 software. The GEOBIA process is carried out through three stages, firstly the segmentation to separate residential blocks from surrounding land cover objects (bodies of water, vegetation, open land, non-residential built-up land) as well as exploring the variable values of each object, then sample-based classification using the SVM algorithm on Google Earth Engine application, and accuracy test to evaluate semantic and geometric accuracy levels. The results of the mapping are 3 classes of residential types followed by 4 classes of land cover. The overall accuracy of the three types of residential is 80% which means that the GEOBIA approach is able to show good performance.
MODELING FOREST AND LAND FIRE VULNERABILITY IN BANJAR DISTRICT USING RANDOM FOREST CLASSIFICATION METHOD IN 2023 Wicaksana, Muhammad Akbar; Widayani, Prima; Windartono, Barandi Sapta
JURNAL SOCIUS Vol 14, No 2 (2025): JURNAL SOCIUS
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/js.v14i2.22935

Abstract

Forest and land fires are a major environmental concern in Banjar Regency, South Kalimantan, with a burned area of 1,812.80 ha recorded in 2023. This study aims to model fire susceptibility levels using the Random Forest algorithm based on remote sensing data. The data utilized include Landsat 8 imagery from 2023 with extracted spectral indices such as NDVI, NBR, NDWI, MSI, and BAI, along with fire hotspot data from the Banjar Regency Disaster Management Agency. The model was trained using data from June to mid-September and validated with data from mid-September to November 2023. Results indi-cate that the northern and central areas of Banjar Regency exhibit the highest fire susceptibility. The susceptibility map was categorized into five zones based on fire probability. Accuracy assessment using a confusion matrix yielded an overall accuracy of 71.64% and a Kappa coefficient of 40.81%. These findings demonstrate that the Random Forest method is effective in iden-tifying fire-prone areas with high efficiency and minimal input data. This model provides a valuable tool for spatially targeted fire prevention and mitigation planning.
Hubungan Nilai Indeks Permukaan Terhadap Temperatur Permukaan di Kabupaten Bantul Rachmadhani, Dini; Zalsabilah, Putri; Kamal, Muhammad; Widayani, Prima
Jurnal Pembangunan Wilayah dan Kota Vol 21, No 4 (2025): JPWK Volume 21 No. 4 December 2025
Publisher : Universitas Diponegoro Publishing Group, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/pwk.v21i4.71617

Abstract

Perkembangan kota yang pesat menyebabkan perubahan penggunaan lahan di wilayah sekitarnya, termasuk di Kabupaten Bantul. Penelitian ini bertujuan menganalisis hubungan antara  Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), Bare Soil Index (BSI), terhadap  Land Surface Temperature (LST) menggunakan data citra satelit Landsat serta teknik pemodelan spasial selama periode 2014, 2019, dan 2024. Hasil penelitian menunjukkan bahwa nilai NDVI, NDBI, dan BSI dan LST mengalami fluktuasi tahunan berdasarkan perekaman tahun 2014, 2019, dan 2024. Hubungan NDVI dan LST menunjukkan korelasi negatif, dengan nilai R² tertinggi sebesar 0,5819 pada tahun 2014, yang mengindikasikan semakin tinggi NDVI, maka suhu permukaan tanah cenderung lebih rendah. Sedangkan, NDBI menunjukkan korelasi positif terhadap LST, dengan nilai R² tertinggi sebesar 0,5312 pada tahun 2014. Hubungan BSI terhadap LST juga menunjukkan korelasi positif, di mana semakin tinggi nilai BSI, suhu permukaan tanah semakin meningkat, khususnya pada tahun 2014, 2019, dan 2024.
Socioeconomic, Spatial, and Infrastructural Determinants of Health among Single Older Women: A Descriptive Analysis Bratanegara, Alnidi Safarach; Pitoyo, Agus Joko; Widayani, Prima; Hizbaron, Dyah Rahmawati; Perdani, Agni Laili; Koa, Apryadno Jose Al Freadman
Jurnal Pendidikan Keperawatan Indonesia Vol 11, No 2 (2025): Volume 11, Nomor 2, Desember 2025
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jpki.v11i2.90434

Abstract

Introduction: The aging population presents significant global challenges, especially in developing countries such as Indonesia. In West Java Province, Tasikmalaya Regency has the highest number of single female elderly, a group more vulnerable to physical and social isolation, which affects their health status. Objective: This study aims to assess the health level of single female elderly in Tasikmalaya Regency using the Activity of Daily Living (ADL) instrument, and analyze the impact of socio-economic, spatial, and infrastructural factors on their health. Method: A mixed-method approach was applied, combining quantitative surveys using the Older Americans Resources and Services (OARS) ADL instrument with qualitative interviews. A total of 383 respondents were selected through cluster sampling across 39 subdistricts. Spatial analysis using GIS was employed to map health disparities by topography. Result: The findings show that most respondents fall within the “Good” and “Mildly Impaired” health categories, based on ADL scores. Elderly women in lowland areas have better ADL scores compared to those in hilly or mountainous regions due to better accessibility to healthcare facilities. The data also reveal that single elderly women are highly dependent in instrumental ADL activities such as medication management and financial handling, while they show higher independence in basic physical ADL tasks like eating, bathing, and dressing. Conclusion: The ADL instrument proves effective in evaluating the health status of elderly individuals and reflects their level of independence. Geographic and infrastructural factors play a critical role in shaping health outcomes, particularly in rural and topographically challenging areas. These results highlight the urgent need for inclusive health policies and long-term care strategies to address accessibility gaps for single elderly women in Indonesia.
Mapping Malaria Risk in Jayapura Using a Random Forest Approach Rumbiak, Mutiara Sanggita Is; Widayani, Prima; Widartono, Barandi Sapta
Jurnal Kesehatan Vokasional Vol 11, No 1 (2026): February
Publisher : Sekolah Vokasi Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jkesvo.113636

Abstract

Background: Malaria remains a major health issue in Jayapura, where climatic and landscape variability creates uneven transmission risks. Early identification of vulnerable areas is essential for supporting targeted control strategies.Objective: This study aims to develop a Random Forest model integrating remote-sensing environmental variables to identify malaria-prone areas in Jayapura District and Jayapura City.Methods: Environmental predictors including rainfall, land surface temperature, slope, NDVI, humidity, land use, and population density were linked to confirmed malaria cases. Data were split into 70% training and 30% testing datasets. Model performance was evaluated using accuracy, sensitivity, macro-sensitivity, and macro-specificity, and the outputs were used to generate a spatial malaria risk map.Results: The Random Forest model achieved an overall accuracy of 0.667, sensitivity of 0.833, macro-sensitivity of 0.800, and macro-specificity of 0.867, indicating good capability in identifying areas with higher malaria vulnerability. Feature importance analysis showed that rainfall, land surface temperature, and slope were the most influential predictors of malaria risk. High-risk areas were concentrated in coastal and urban zones, while peri-urban agricultural areas showed moderate risk and high-elevation regions exhibited lower vulnerability.Conclusion: Integrating remote-sensing environmental data with epidemiological information allows the Random Forest model to capture key malaria-risk patterns in Jayapura. The resulting spatial risk map can support targeted vector control strategies, improved surveillance, and more efficient allocation of public health resources toward Indonesia’s Malaria Elimination 2030 goals. 
Application of Remote Sensing and GIS Using The Analytical Hierarchy Process for Malaria Vulnerability Modeling : A Learning Case from Jayapura, Indonesia Mutiara Sanggita Is Rumbiak; Prima Widayani; Barandi Sapta Widartono
JURNAL SOCIUS Vol 15, No 1 (2026): JURNAL SOCIUS
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/js.v15i1.25249

Abstract

Malaria remains a major vector-borne disease and a persistent public health problem in Papua Province, Indonesia, particularly in Jayapura Regency and Jayapura City. This study applies remote sensing and Geographic Information Systems (GIS) integrated with the Analytical Hierarchy Process (AHP) to model malaria vulnerability, while presenting the analysis as a learning case for geospatial-based health studies. Spatial data derived from Landsat 8 OLI, SRTM, CHIRPS, meteorological observations, and official population and malaria records were analyzed using pairwise comparison and weighted overlay techniques. The results indicate that high malaria vulnerability is predominantly associated with lowland and coastal areas characterized by high rainfall, high humidity, and relatively high population density. The resulting vulnerability map shows strong spatial correspondence with reported malaria cases and is easily interpretable. Overall, this study demonstrates that AHP-based remote sensing and GIS analysis not only supports malaria vulnerability assessment but also provides an effective instructional framework for teaching spatial decision-making in environmental and geographic health education.
Hubungan Nilai Evapotranspirasi Metode Penman-Monteith dengan Indeks Vegetasi di Sebagian Wilayah Provinsi DI Yogyakarta dan Jawa Tengah Tahun 2024 Dini Rachmadhani; Projo Danoedoro; Prima Widayani; Sigit Heru Murti Budi Santosa; Sandy Budi Wibowo
Media Komunikasi Geografi Vol. 27 No. 1 (2026)
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/mkg.v27i1.110080

Abstract

Alih fungsi lahan di wilayah Daerah Istimewa Yogyakarta dan Jawa Tengah dari area bervegetasi menjadi kawasan terbangun berpengaruh terhadap siklus hidrologi, khususnya pada proses evapotranspirasi. Salah satu parameter yang dapat digunakan untuk merepresentasikan kondisi vegetasi adalah indeks vegetasi, seperti Normalized Difference Vegetation Index (NDVI) dan Soil Adjusted Vegetation Index (SAVI). Penelitian ini bertujuan untuk menganalisis hubungan antara evapotranspirasi yang dihitung menggunakan metode Penman–Monteith dengan indeks vegetasi NDVI dan SAVI. Metode penelitian meliputi analisis spasial menggunakan citra Landsat 8 tahun 2024, analisis statistik, serta pendekatan konvensional berdasarkan data meteorologi dari Badan Meteorologi, Klimatologi, dan Geofisika (BMKG). Hasil penelitian menunjukkan bahwa hubungan antara NDVI dan evapotranspirasi memiliki nilai koefisien korelasi Pearson sebesar 0,157 dengan nilai signifikansi 0,801, sedangkan hubungan antara SAVI dan evapotranspirasi menghasilkan nilai koefisien Pearson sebesar 0,136 dengan nilai signifikansi 0,828. Kedua hasil tersebut menunjukkan bahwa hubungan yang diperoleh tergolong sangat lemah dan tidak signifikan secara statistik, dinamika evapotranspirasi di wilayah dengan lanskap heterogen tidak dapat dijelaskan hanya oleh indeks vegetasi, melainkan memerlukan pendekatan yang mempertimbangkan interaksi kompleks antara vegetasi, iklim, dan karakteristik fisik wilayah.
Integrasi Penginderaan Jauh dan Random Forest untuk Pemodelan Kerawanan Kebakaran di Taman Nasional Bromo Tengger Semeru Dhia Aufa Sabila; Sigit Heru Murti Budi Santosa; Prima Widayani
Media Komunikasi Geografi Vol. 27 No. 1 (2026)
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/mkg.v27i1.113260

Abstract

Kebakaran hutan dan lahan merupakan bencana ekologis yang berulang di Indonesia, terutama pada periode musim kemarau. Peningkatan frekuensi dan intensitas kebakaran diperlukan mekanisme pencegahan yang lebih efektif berbasis informasi spasial mengenai wilayah rawan untuk mengurangi potensi dan dampaknya. Integrasi data penginderaan jauh yang merepresentasikan kondisi vegetasi, iklim, topografi, dan faktor antropogenik dengan pemodelan berbasis pembelajaran mesin menjadi pendekatan yang relevan untuk memetakan kerawanan kebakaran secara objektif dan terukur. Penelitian ini bertujuan mengevaluasi kinerja algoritma Random Forest (RF) dalam memodelkan probabilitas kerawanan kebakaran hutan dan lahan serta mengidentifikasi faktor-faktor dominan yang memengaruhinya melalui analisis variable importance berbasis Mean Decrease in Gini di kawasan Taman Nasional Bromo Tengger Semeru (TNBTS). Hasil penelitian menunjukkan bahwa model RF menghasilkan nilai AUC sebesar 0,948, yang mengindikasikan kemampuan diskriminatif sangat baik dalam membedakan area rawan dan tidak rawan kebakaran. Elevasi menjadi prediktor paling dominan dengan kontribusi sebesar 20,23%, diikuti oleh NDVI sebesar 11,51% dan Potential Evapotranspiration sebesar 10,16%. Temuan ini menunjukkan bahwa interaksi topografi, kondisi vegetasi, dan tekanan kekeringan merupakan pengontrol utama kerawanan kebakaran di TNBTS. Sementara itu, variabel aspect dan jarak terhadap sungai menunjukkan kontribusi terendah terhadap model. Hasil pemetaan menunjukkan bahwa kawasan dengan tingkat kerawanan tinggi mencakup 10.523,12 ha, sedangkan kelas kerawanan sangat tinggi mencakup 3.666,36 ha. Secara keseluruhan, penelitian ini menunjukkan bahwa RF merupakan pendekatan yang andal untuk pemetaan kerawanan kebakaran hutan dan lahan berbasis penginderaan jauh, sekaligus menyediakan dasar empiris bagi perumusan strategi pencegahan, pengawasan, dan mitigasi kebakaran yang lebih terarah pada skala operasional kawasan konservasi.
Co-Authors Achmad Fadhilah Achmad Fadilah Ade Febri Sandhini P Agatha Andriantari Agus Joko Pitoyo Agus Joko Pitoyo Akmal Hafiudzan Akmal Hafiudzan Alnidi Safarach Bratanegara Andung Bayu Sekaranom Arief Wicaksono Arrafi, Muhammad Bagus Wiratmoko Barandi Sapta Widartono Bowo Susilo Dewi Miska Indrawati Dhia Aufa Sabila Dini Rachmadhani Dyah Kusuma, Dyah Edi Suharyadi Erika Yuliantari Fadilah, Achmad Fathilda, Intan Khaeruli Febrianti, Ni Kadek Oki Ghosh, Kapil Hamim Zaky Hadibasyir Hari Kusnanto Hidayatullah, Faqih Hizbaron, Dyah Rahmawati Huwaida Nur Salsabila Indrawati, Dewi Miska Ira Nurmala Hani Irawan, Irfan Zaki Irfan Zaki Irawan Irfan Zaki Irawan Irsan, Laode Muhamad Iswari Nur Hidayati Kapil Ghosh Koa, Apryadno Jose Al Freadman Kusbaryanto Mahendra, Auzaie Ihza Mizan, Rahmat azul Muhammad Arrafi Muhammad Kamal Muhammad Kamal Muhammad Minan Chusni Muhammad Sufwandika Wijaya Muhammad Sufwandika Wijaya Muhammad Sufwandika Wijaya Murti Budi Santosa, Sigit Heru Mutiara Sanggita Is Rumbiak Ni Kadek Oki Febrianti Nur Mohammad Farda Nur Mohammad Farda Nurbandi, Wahyu Nurhadi, Muhammad Nurul Astuti, Nurul Nurweni, Susi Nurwita Mustika Sari Nurwita Mustika Sari Perdani, Agni Laili Projo Danoedoro Projo Danoedoro Projo Danoedoro R. Suharyadi Rachmadhani, Dini Ramadhan Pasca Wijaya Rina Febriany Rumbiak, Mutiara Sanggita Is Sandy Budi Wibowo Sandy Budi Wibowo Sanjiwana Arjasakusuma Sanjiwana Arjasakusuma, Sanjiwana Santosa, Sigit Herumurti Budi Seandrasto Abi Kharis Wardhani Shandra S Pertiwi Sigit Heru Murti Siti Zahrotunisa Sitti Rahmah Umniyati Sudaryatno Sudaryatno Sugeng Juwono Mardihusodo Suherningtyas, Ika Afianita Totok Gunawan Totok Wahyu Wibowo Tri Wulandari Kesetyaningsih Ulfa Aulia Syamsuri Vandam Caesariadi Bramdito Wahyu Nurbandi Wicaksana, Muhammad Akbar Windartono, Barandi Sapta Wiratmoko, Bagus Wirayuda, I Kade Alfian Kusuma Zalsabilah, Putri