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All Journal International Journal of Public Health Science (IJPHS) Indonesian Journal of Geography Geo Media: Majalah Ilmiah dan Informasi Kegeografian 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 GEA, Jurnal Pendidikan Geografi Jurnal Fisika FLUX Journal of Applied Geospatial Information Jurnal Geografi Forest and Society International Journal of Remote Sensing and Earth Sciences (IJReSES) JAGAT (Jurnal Geografi Aplikasi dan Teknologi) Jurnal Geosains dan Remote Sensing (JGRS) geoedusains: Jurnal Pendidikan Geografi GEOGRAPHIA: Jurnal Pendidikan dan Penelitian Geografi Proceeding ISETH (International Summit on Science, Technology, and Humanity) Jurnal Manusia dan Lingkungan Aerospace Engineering IJES : Indonesian Journal of Environmental Sustainability.
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 Physics Social Sciences Other

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PENGGUNAAN SPATIAL MULTICRITERIA ANALYSIS UNTUK MENENTUKAN DAERAH RAWAN MALARIA DI KABUPATEN PURWOREJO (Application of Spatial Multicriteria Analysis Determining Malaria Vulnarable Area in Purworejo Regerency) Prima Widayani; Erika Yuliantari
Jurnal Manusia dan Lingkungan Vol 24, No 2 (2017): Mei
Publisher : Pusat Studi Lingkungan Hidup Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jml.24819

Abstract

AbstrakMalaria merupakan salah satu penyakit menular endemis yang masih menjadi perhatian khusus pada kesehatan masyarakat di Indonesia, salah satunya di Kabupaten Purworejo. Tahun 2013, terdapat 615 kasus kejadian penyakit malaria pada semua rentang umur di kabupaten ini. Penanganan penyakit ini dilakukan dengan beberapa cara, contohnya adalah dengan surveilans malaria. Kegiatan surveilans bermaksud untuk melaksanakan tindakan penanggulangan yang cepat dan akurat disesuaikan dengan kondisi setempat. Salah satu tujuan kegiatan ini untuk mendapatkan gambaran distribusi penyakit malaria yang dapat dilakukan dengan pembuatan peta kerawanan penyakit malaria. Tujuan dari penelitian ini adalah menentukan kerawanan wilayah terhadap penyakit malaria dengan metode Spatial Multicriteria Analysis (SMCA). Penelitian ini memanfaatkan data Citra Landsat 8 dan beberapa data sekunder yang diolah dengan menggunakan software ILWIS. Hasil dari penelitian ini menunjukan bahwa metode SMCA dapat memetakan kerawanan penyakit malaria dan terdapat enam kecamatan di Kabupaten Purworejo yang rawan, yaitu Kecamatan – kecamatan Bruno, Bener, Gebang, Loano, Kaligesing, dan Bagelen.AbstractMalaria is one of endemic infectious disease that has been special concern in Indonesian public health, especially in Purworejo Regency. In 2013, there were 615 incident cases of malaria disease in all age ranges. There are several kinds of handling malaria disease, one of which is malaria surveillances. Surveillances activity intends to implement handling fast and accurate actions. One of this activity aims to obtain overview distribution of malaria disease which can be done with vulnerable mapping. This study aims to determine vulnerability of area with malaria disease using Spatial Multicriteria Analysis (SMCA). It has been done by utilizing Landsat 8 Imagery data and some of secondary data processing with ILWIS software. The result of this study showed that SMCA methods can be used to vulnerability mapping of malaria disease and found that there are six vulnerable districts, Bruno, Bener, Gebang, Loano, Kaligesing, and Bagelen District.
Implementing Support Vector Machine Algorithm for Early Slum Identification in Yogyakarta City, Indonesia Using Pleiades Images Prima Widayani; Achmad Fadilah; Irfan Zaki Irawan; Kapil Ghosh
Forum Geografi Vol 37, No 1 (2023): July 2023
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v37i1.15248

Abstract

Slums are one of the urban problems that continue to get the attention of the government and the city of Yogyakarta. Over time, cities continue to experience changes in land use due to population growth and migration. Therefore, it is necessary to monitor the existence of slums continuously. The objectives of this study are to conduct early identification of the slum using the Support Vector Machine (SVM) Algorithm, which is applied to the Pleiades Image in parts of Yogyakarta City, to test the accuracy of the slum mapping results generated from the SVM compared to the Slum Map of the KOTAKU Program. The data used are Pleiades Image, administrative maps, and existing slum maps of the KOTAKU Program, which are used to test the accuracy. The method used is Machine Learning with a Support Vector Machine Algorithm. The parameters used for early identification of the slums are the characteristics of the object (characteristics of buildings), settlement (density and shape), and the environment (location and its proximity to rivers and industries). We separate slum and non-slum based on texture, morphology, and spectral approaches. Based on the accuracy test results between the SVM classification results map of the slum and the map from the KOTAKU Program, the accuracy is 86.25% with a kappa coefficient of 0.796.
Spatial Analysis of Economic Resilience in Urban Areas During the COVID-19 Pandemic (Case Study: Wonosari, Gunungkidul, Indoensia) Analisis Spasial Ketahanan Ekonomi di Wilayah Perkotaan selama Pandemi COVID-19 (Studi Kasus: Kecamatan Wonosari Kabupaten Gunungkidul Provinsi Daerah Istimewa Yogyakarta) Ika Afianita Suherningtyas; Agus Joko Pitoyo; Prima Widayani
Jurnal Ketahanan Nasional Vol 29, No 2 (2023)
Publisher : Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jkn.85042

Abstract

ABSTRACTThe COVID-19 pandemic has led to a decline in the national and international economies. This research aimed to determine the spatial analysis of economic resilience in urban areas during the COVID-19 pandemic, using Wonosari District in Gunungkidul, Indonesia, as an example. The mixed-method design of the analytic hierarchy process (AHP) was used to determine the weight of each factor of economic resilience, which included expert judgment (qualitative). Then, the geographic information system (GIS) was used as a tool to spatially characterize economic resilience using descriptive analysis. AHP showed six factors of economic resilience: socioeconomic condition, community, infrastructure, institution, natural resources, and technology and communication. The most determining factor was socioeconomic condition (weight: 0.283, rank 1), while the least influencing factor was infrastructure condition (weight: 0.112, rank 6). Based on data distribution, Wonosari had medium economic resilience in eight villages (accounting for 57% of the total area), high resilience in four villages (29%), and low resilience in two villages (14%). Although Wonosari is generally economically resilient with variation charachteristic, collaborations between stakeholders, including the community, government, organizations, and academics, are needed to enhance this condition.ABSTRAKPandemi COVID-19 mengakibatkan penurunan kondisi ekonomi nasional dan internasional. Penelitian ini bertujuan untuk melakukan analisis spasial terhadap ketahanan ekonomi wilayah perkotaan pada masa pandemi, khususnya di Kecamatan Wonosari, Gunungkidul, Indonesia.Metode penelitian ini memanfaatkan pendekatan kuantitatif dan kualitatif pada Analytic Hierarchy Process (AHP) untuk menentukan bobot faktor ketahanan ekonomi, termasuk menggunakan pendapat para ahli (expert judgement). Selanjutnya, dilakukan analisis spasial dengan tools Sistem Informasi Geografis (SIG) untuk mendeskripsikan karakter spasial atau keruangan ketahanan ekonomi di lokasi penelitian.Hasil AHP menunjukkan enam faktor ketahanan ekonomi, yaitu kondisi sosial ekonomi, masyarakat, infrastruktur, kelembagaan, sumber daya alam, serta teknologi dan komunikasi. Faktor terpenting (peringkat pertama) adalah sosial ekonomi dengan bobot 0,283, sedangkan faktor dengan pengaruh terkecil (peringkat terakhir) adalah kondisi infrastruktur dengan bobot 0,112. Sebaran klasifikasi menunjukkan bahwa Wonosari memiliki kelas ketahanan ekonomi sedang yang meliputi 57% dari total area (delapan desa), kelas tinggi seluas 29%, dan kelas rendah seluas 14%. Meskipun Wonosari secara umum memiliki ketahanan ekonomi yang bervariasi, namun tetap diperlukan kerjasama antar pemangku kepentingan, termasuk masyarakat, pemerintah, organisasi, dan akademisi, untuk meningkatkan kondisi ketahanan ekonomi saat ini
Dampak Perubahan Penutup dan Penggunaan Lahan Terhadap Nilai Jasa Ekosistem di Kabupaten Sleman Prima Widayani; Huwaida Nur Salsabila; Agatha Andriantari
Majalah Geografi Indonesia Vol 37, No 2 (2023): Majalah Geografi Indoenesia
Publisher : Fakultas Geografi, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/mgi.78192

Abstract

Perubahan penutup dan penggunaan lahan di suatu wilayah adalah sebuah keniscayaan, konsisi ini juga terjadi di Kabupaten Sleman Daerah Istimewa Yogyakarta. Pada dasarnya penutup penggunaan lahan merupakan bagian dari ekosistem yang bisa dihitung nilai jasa ekosistemnya. Penelitian ini bertujuan untuk memetakan penutup dan penggunaan lahan dan menganalisi dampak perubahan penututup penggunaan lahan terhadap nilai jasa ekosistem di Kabupaten Sleman pada tahun 1991, 2001, 2013 dan 2022. Data utama yang digunakan adalah Citra Satelit Landsat 5 tahun 1991, Landsat 7 tahun 2001, Landsat 8 tahun 2013 dan Landsat 9 tahun 2022. Klasifikasi multispektral supervised dengan algoritma maksimum likelihood digunakan untuk mendapatkan data penutup dan penggunaan lahan. Berdasarkan hasil klasifikasi penutup dan penggunaan lahan selama kurun waktu 31 tahun, lahan terbangun memiliki nilai landuse dynamic index (K) paling tinggi yaitu 4,5%. Penutup lahan yang paling stabil hanya sedikit mengalami perubahan adalah tubuh air dan lahan pertanian. Perubahan penutup dan penggunaan lahan memiliki dampak terhadap nilai jasa ekosistem dengan nilai elastisitas sebesar 0,4% dari tahun 1991-2022.
Mapping of Mangrove Composition in Ratai Bay, Lampung Province using Pleiades 1 Satellite Imagery Muhammad Sufwandika Wijaya; Muhammad Kamal; Prima Widayani
Jurnal Pendidikan Geografi Gea Vol 23, No 2 (2023)
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/gea.v23i2.59612

Abstract

Mangroves are vegetation with significant value in the coastal areas of Indonesia, protected through recognition as protected areas and national rehabilitation programs. In support of these efforts, information on mangrove composition distribution is crucial for biodiversity inventory in mangrove ecosystems. Remote sensing technology, such as Pleiades 1 satellite imagery, can map mangroves down to the family level. On the other hand, Teluk Ratai in Lampung has a well-established natural mangrove ecosystem within a protected area, but limited information is available regarding the composition of vegetation types within it. Therefore, this research aims to map the mangrove vegetation composition in Teluk Ratai using Pleiades 1 satellite imagery. The mapping method involves image segmentation and unsupervised classification to categorize the study area into vegetation classes for field surveys. The final vegetation composition classes are obtained through reclassification based on a key photo approach constructed from field data. The classification represents dominant lifeforms and species. The mapping results of mangrove composition in Teluk Ratai using Pleiades 1 satellite imagery reveal six mangrove composition classes with a total accuracy rate of 92%. The Forest class, dominated by Rhizophora apiculata species, is the largest, covering an area of 203.19 hectares out of the total mangrove area of 277.15 hectares in Teluk Ratai. Additionally, classes dominated by shrubs lifeforms, primarily composed of Rhizophora apiculata and Avicennia marina species, are frequently found in the mudflat areas at the mouth of the Ratai River.
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 (IJReSES) Vol 20, No 2 (2023)
Publisher : Ikatan Geografi Indonesia

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.
Analisis Kualitas Ekologi Perkotaan Berbasis Data Penginderaan Jauh di Kota Bandung Tahun 2023 Auzaie Ihza Mahendra; Sigit Heru Murti Budi Santosa; Prima Widayani
Geomedia: Majalah Ilmiah dan Informasi Kegeografian Vol 22, No 1 (2024): Geo Media: Majalah Ilmiah dan Informasi Kegeografian
Publisher : Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/gm.v22i1.70337

Abstract

Urbanization has consequences for the urban environment, such as environmental pollution, which has a direct impact on the quality of urban ecology. In monitoring the quality of the urban environment, RSEI is one method that can be used. This study aims to assess the quality of urban ecology using RSEI in Bandung City in 2023 during the rainy season and dry season. RSEI combines four main indicators in the form of NDVI, WET, NDBSI, and LST from Landsat 8 and 9 image data analyzed using the PCA method. The results showed that image recording in both seasons greatly affected the RSEI results, where RSEI had better conditions during the rainy season than the dry season in terms of area and spatial distribution. This was evidenced by the RSEI area in the good and very good categories tending to be higher during the rainy season.Keywords: Urban Ecological Quality, RSEI, Landsat
Urban Green Space Analysis and its Effect on the Surface Urban Heat Island Phenomenon in Denpasar City, Bali Wirayuda, I Kade Alfian Kusuma; Widayani, Prima; Sekaranom, Andung Bayu
Forest and Society Vol. 7 No. 1 (2023): APRIL
Publisher : Forestry Faculty, Universitas Hasanuddin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24259/fs.v7i1.24526

Abstract

The Urbanization process in Indonesia’s big cities causes adverse environmental impacts such as climate change and land cover change. Urban climate change causes the warming of urban areas compared to rural areas; it is called Urban Heat Island phenomenon. Loss of vegetation due to urban development is one of several causes that contribute to urban heat islands. This study examines the availability of green spaces and their effects on the surface urban heat island in Denpasar city. This study used the spatial approach for Urban Green space mapping with digitizing methods. Landsat 8's thermal band is used for land surface temperature mapping and to conduct a spatial pattern analysis of the SUHI phenomena. The Global Moran’s Index and Local Indicator of Spatial Association (LISA) were used to determine the correlation between urban green space and SUHI. The study result shows that Denpasar City's urban green space area covers 28.22 km2. That's equal to 22.1% of the Denpasar City Administrative area. Denpasar Selatan district has the largest urban green space cover, with 14.19 km2 covered, or 50.27% of all the green space in Denpasar City. The majority of Denpasar is affected by UHI occurrences, except the northern region of North Denpasar and the southern region of South Denpasar. The maximum UHI level reaches 4-5°C, located on the east side of South Denpasar, especially in the Sanur coastal area. According to the spatial pattern study, the association between urban green space and SUHI only exists on the north side of Denpasar. The correlation between low-SUHI intensity clusters and high cover of green space is shown in the same area. However, the association between High-UHI intensity and low green space cover has not significantly happened. It indicated that other factors besides green space could affect the land surface temperature.
Dengue hemorrhagic fever prediction in coastal area using geographically weighted regression Kesetyaningsih, Tri Wulandari; Kusbaryanto, Kusbaryanto; Widayani, Prima
International Journal of Public Health Science (IJPHS) Vol 13, No 2: June 2024
Publisher : Intelektual Pustaka Media Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijphs.v13i2.23304

Abstract

Dengue hemorrhagic fever (DHF) is still a health problem globally, including in Indonesia. Geographical and climatic conditions in coastal areas are different from other areas, which may impact differences in environmental risk factors for dengue. This study aims to create a prediction model for the incidence of DHF in coastal areas. The research was conducted in Bantul Regency, Indonesia, involving data from 2015-2019. Dengue incidence data were collected from the health office. Climatic data were from climatology station. Data on altitude and shoreline distance were obtained by geographic information system (GIS) processing. Population density and wide settlement area are obtained from the Bureau of Statistics. The geographically weighted regression (GWR) analysis was carried out using GWR4. The results showed that GWR with a weighting of Fixed Bi-Square Kernel obtained an R2 value of 0.7768, better than the global model (R2 0.5254). It indicates that DHF (Y) in Bantul Regency is 77.68% determined by population density (X1), altitude (X2), settlement area (X3), shoreline distance (X4) and rainfall (X5) and the remaining 22.32% are influenced by other variables which are not investigated. Geographically, the predictor variables explain the DHF incidence with a strong category in the central region, and weak in coastal area.
Classification of Mangrove Vegetation Structure using Airborne LiDAR in Ratai Bay, Lampung Province, Indonesia Wijaya, Muhammad Sufwandika; Kamal, Muhammad; Widayani, Prima; Arjasakusuma, Sanjiwana
Geoplanning: Journal of Geomatics and Planning Vol 10, No 2 (2023)
Publisher : Department of Urban and Regional Planning, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/geoplanning.10.2.123-134

Abstract

Mapping and inventory of the distribution and composition of mangrove vegetation structures are crucial in managing mangrove ecosystems. The availability of airborne LiDAR remote sensing technology provides capability of mapping vegetation structures in three dimensions. It provides an alternative data source for mapping and inventory of the distribution of mangrove ecosystems. This study aims to test the ability of airborne LiDAR data to classify mangrove vegetation structures conducted in Ratai Bay, Pesawaran District, Lampung Province. The classification system applied integrates structure attributes of lifeforms, canopy height, and canopy cover percentage. Airborne LiDAR data are derived into canopy height models (CHM) and canopy cover percentage models, then grouped by examining statistics and the zonation distribution of mangroves in the study area. The results of this study show that airborne LiDAR data are able to map vegetation structures accurately. The canopy height model derived using a pit-free algorithm can represent the maximum tree height with an error range of 3.17 meters and 82.3-88.6% accuracy. On the other hand, the canopy cover percentage model using LiDAR Fraction Cover (LFC) tends to be overestimate, with an error range of 16.6% and an accuracy of 79.6-94.7%. Meanwhile, the classification results of vegetation structures show an overall accuracy of 77%.
Co-Authors Achmad Fadhilah Achmad Fadilah Ade Febri Sandhini P Agatha Andriantari Agus Joko Pitoyo Akmal Hafiudzan Andung Bayu Sekaranom Arief Wicaksono Arrafi, Muhammad Auzaie Ihza Mahendra Bagus Wiratmoko Bowo Susilo Dewi Miska Indrawati Dyah Kusuma, Dyah Edi Suharyadi Erika Yuliantari Fathilda, Intan Khaeruli Hamim Zaky Hadibasyir Hari Kusnanto Hidayatullah, Faqih Huwaida Nur Salsabila Indrawati, Dewi Miska Ira Nurmala Hani Irfan Zaki Irawan Irfan Zaki Irawan Irsan, Laode Muhamad Iswari Nur Hidayati Kapil Ghosh Kusbaryanto Mizan, Rahmat azul Muhammad Arrafi Muhammad Kamal Muhammad Kamal Muhammad Minan Chusni Muhammad Sufwandika Wijaya Muhammad Sufwandika Wijaya Muhammad Sufwandika Wijaya Nama Penulis Ni Kadek Oki Febrianti Nur Mohammad Farda Nur Mohammad Farda Nurbandi, Wahyu Nurhadi, Muhammad Nurul Astuti, Nurul Nurweni, Susi Nurwita Mustika Sari Projo Danoedoro Projo Danoedoro Projo Danoedoro R. Suharyadi Ramadhan Pasca Wijaya Rina Febriany Sandy Budi Wibowo Sanjiwana Arjasakusuma Sanjiwana Arjasakusuma, Sanjiwana Santosa, Sigit Herumurti Budi Seandrasto Abi Kharis Wardhani Shandra S Pertiwi Sigit Heru Murti 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 Wiratmoko, Bagus Wirayuda, I Kade Alfian Kusuma Zahrotunisa, Siti