Article Per Year (5 Year)
p-Index From 2021 - 2026
4.031
P-Index
This Author published in this journals
All Journal Indonesian Journal of Geography Geoplanning : Journal of Geomatics and Planning Forum Geografi Edukasi: Jurnal Pendidikan Sosial Horizon: Jurnal Pendidikan Sosial Jurnal Penelitian Pendidikan IPA (JPPIPA) Geodika: Jurnal Kajian Ilmu dan Pendidikan Geografi Sosial Khatulistiwa: Jurnal Pendidikan IPS GeoEco Geosfera Indonesia
Ajun Purwanto
PGRI Pontianak University
Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Earth & Planetary Sciences Education Environmental Science Materials Science & Nanotechnology Physics Social Sciences

Published : 32 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 6 Documents
Search
Journal : GeoEco

 1 
PADDY FIELD LAND CHANGE ANALYSIS BASED ON GEOGRAPHY INFORMATION SYSTEM AND REMOTE SENSING IN THE KUBU RAYA DISTRICT Ekawati Ekawati; Rahmatullah Rizieq; Hardi Dominikus Bancin; Ellyta Ellyta; Ajun Purwanto
GeoEco Vol 11, No 1 (2025): GeoEco January 2025
Publisher : Universitas Sebelas Maret (UNS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ge.v11i1.95991

Abstract

Rice plays an important role in ensuring food security worldwide, especially in Southeast Asia and Indonesia. This study aims to determine the changes in paddy field area and spatial distribution of changes in 2019-2024 using Geographic Information Systems and Remote Sensing in Kuburaya Regency. The data used in this study include the area of paddy fields in Kubu Raya Regency in 2019-2024, an Indonesia Biomass Image, and a Topographic map. The data obtained were then processed using ArcGIS Pro software. Data analysis used a geoprocessing tool with the clip, Intersect, and Dissolve tools and Spatial Analysis using the Map Algebra Tool. The study results showed that overall changes in paddy field area from 2019-2023 were 9036,88 ha. Of the fourteen villages in the Teluk Pakedai sub-district, eight villages experienced an increase in area. The villages are Sungai Nibung, Kuala Karang, Seruat Satu, Tanjung Bunga, Teluk Pakedai Hulu, Madura, Sungai Nipah, and Teluk Pakedai Satu. Overall, the eight villages experienced an increase in the paddy field area of 578.94 ha or 21% of the total area in 2024. Two villages, namely Sungai Nibung and Kuala Karang experienced a 100% increase from 2019. The Geographic Information System and Remote Sensing provide convenience in monitoring and analyzing changes in land use, in this case, changes in the area of paddy fields. Therefore, in the future, this technology will be more effective in its use, because with this technology the data will be easy to update.
GEOGRAPHICAL INFORMATION SYSTEM BASED COVID-19 VULNERABILITY MAPPING IN PONTIANAK REGENCY WEST KALIMANTAN Ajun Purwanto; Yoga Prasetya Adi Nugraha
GeoEco Vol 9, No 1 (2023): GeoEco January 2023
Publisher : Universitas Sebelas Maret (UNS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ge.v9i1.60660

Abstract

2020 was the start of the toughest year for the world community in general, especially Indonesia in the health sector. The outbreak of the Covid-19 case in various regions requires clear and accurate information in efforts to deal with this pandemic. This study aims to spatially map the vulnerability of COVID-19 based on Geographic Information Systems (GIS). The method d used is a weighted overlay. The data used are population (P), population density (PD), elderly (EP), school students (SS), and hospital beds (HB). The analysis s used is a spatial analysis using ArcGIS 10.8. The results of the study show that North Pontianak District has a very high vulnerability to COVID-19. West Pontianak District and Pontianak City have high vulnerability. South and East Pontianak sub-districts have moderate vulnerability. For Pontianak Tenggara District, the level of vulnerability to COVID-19 is very low. The vulnerability to COVID is very low in Southeast Pontianak District because it has the smallest population, low density, few elderly people, few school-age children, and lots of hospital beds. An information system is an effective tool in conveying information on the spatial distribution of the level of vulnerability of Covid-19 in an area, so that steps and handling policies can be  taken according to existing priorities.
ANALYSIS OF MATERIAL LOSS DUE TO FLOOD DISASTER IN THE SUB-DISTRICT OF SILAT HULU, KAPUAS HULU REGENCY Holifah Nurfitri; Florensia Rintia; Francista Francista; Ayu Rianingsih; Nurul Ramdhania; Ajun Purwanto; Dony Andrasmoro; Eviliyanto Eviliyanto
GeoEco Vol 9, No 1 (2023): GeoEco January 2023
Publisher : Universitas Sebelas Maret (UNS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ge.v9i1.62423

Abstract

A flood is a frequent disaster during the rainy season and causes many losses, good materials, treasure objects, and casualties. The study aims to know the loss of materials caused by disasters that flood Bandang in the Silat Hulu Sub-district. The method of research used is descriptive quantitative. Collected data is secondary data, including damaged buildings, facilities and infrastructure, and land. The method analysis used is descriptive. The study results show that The Silat Hulu Sub-district experienced twice the floods successively. The first occurred on 18-19 October 2021 and 22-23 October 2021. A total of 11 villages of 14 villages experience a flood. Consequently, the flood and loss of materials, including dozens of house inhabitants of Village Selangkai and Entebi, were damaged, collapsed, and swept away. A total of 1,813 families were evacuated, and the total loss consequence flood around Rp. 20,000,000.00-30,000,000.00.
MANGROVE HEALTH ANALYSIS USING SENTINEL-2A IMAGE WITH NDVI CLASSIFICATION METHOD Ajun Purwanto; Eviliyanto Eviliyanto
GeoEco Vol 8, No 1 (2022): GeoEco January 2022
Publisher : Universitas Sebelas Maret (UNS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ge.v8i1.51948

Abstract

This study aims to determine 1) the mangrove vegetation density index, 2) the health of mangrove plants in Sungai Batang Village to Kuala Secapah. The data used in this study is the image of Sentinel-2A, dated June 8, 2020. The data taken are vegetation density (NDVI) and mangrove health. The method in this study uses the vegetation index transformation (NDVI). Data analysis used the supervised classification method and the vegetation density index (NDVI). The results showed that the NDVI value of -1 – 0.32 indicates a sparse vegetation density, a value of 0.33 – 0.42 indicates a medium density and 0.43 – 1 indicates a dense density. From this NDVI index value, it can be used as a basis for classifying the health of mangrove vegetation. The health of mangrove vegetation based on the vegetation index value of 0.43 – 1 (meet) indicates that the health of the mangrove vegetation is very good. Vegetation value 0.33 – 0.42 (moderate) indicates good health of mangrove vegetation and vegetation index value -1 – 0.32 (rare) indicates poor vegetation health. Mangrove health level is very good with an area of 3.0314 km2, healthy has an area of 0.204806 km2 and poor health has an area of 0.625875 km2.
MORPHOMETRY ANALYSIS OF SILAT SUB-WATERSHED BASED ON GEOSPATIAL TECHNOLOGY IN THE SILAT HULU SUB DISTRICT Nurul Ramdhania; Ayu Rianingsih; Holifah Nurfitri; Ajun Purwanto; Dony Andrasmoro; Eviliyanto Eviliyanto; Francista Francista; Florensia Rentia
GeoEco Vol 9, No 1 (2023): GeoEco January 2023
Publisher : Universitas Sebelas Maret (UNS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ge.v9i1.60711

Abstract

This study aims to obtain morphometric data from the Silat sub-watershed. The method used is a survey and interpretation of secondary data. Secondary data is taken from Remote Sensing Images, Topographic Maps, and Administration maps. The morphometric data taken were the area, shape, circumstance, river length, river order, height, and drainage density. Data analysis using the Spatial Analyst Tool, namely Hydrology, Map Algebra, and Density tools from ArcGis 10.8. Based on the research results, it is known that the Silat watershed has an area of 466 km², a circumference of 147 km, and a river length of 51 km. The shape of the Silat watershed is elongated because the Circularity Ratio value is 0.27 (<0.5), and the Elongation Ratio value is 5.14 (round). The order of the river network is up to order 6, with a branching index (Rb) of order 1 = 2.03; 2nd order = 2.09; 3rd order = 1.75; 4th order = 1.84; and 5th order = 0.96. The Weighted Average Branching Index (WRb) was 2.73 (<3). The Silat sub-watershed has a height of 32 - 255 meters above sea level. Low river density, dendritic river flow pattern. 
USING SENTINEL-2 IMAGE FOR MANGROVE HEALTH ANALYSIS IN BAKAU KECIL VILLAGE, MEMPAWAH DISTRICT, WEST KALIMANTAN Ajun Purwanto; Paiman Paiman
GeoEco Vol 10, No 2 (2024): GeoEco July 2024
Publisher : Universitas Sebelas Maret (UNS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ge.v10i2.72707

Abstract

This study aims to determine 1) The index of mangrove plant vegetation density, and 2) the state of the mangrove plants in the village of Bakau Kecil. Transforming the NDVI was the method employed in this study. The canopy density model can be applied using NDVI. The degree of vegetation canopy density was correlated with the intensity of greenness. The outcomes demonstrated that NDVI values ranged from -1 to 0.32, indicating sparse vegetation density, 0.33 to 0.42, indicating medium density values, and 0.43 to 1, indicating dense density values. One can categorize the condition of the mangrove vegetation based on the NDVI index value, which is shown above. Based on a vegetation index value of 0.43 - 1, which indicates very good health, mangrove vegetation can be considered to be in excellent condition. The mangrove vegetation is in good health (vegetation value 0.33-0.42, Moderate), and the vegetation is in poor health (vegetation value -1-0.32, Rare), according to the vegetation index. Mangrove health is very good, with a pixel area percentage of 68.88 percent; good health has a pixel area percentage of 23.98 percent; and poor health has a pixel area percentage of 7.14 percent. 
Co-Authors Adella Rahayu Pangestu Agus Sudiro Arif Rohman Ayu Rianingsih Ayu Rianingsih Dony Andrasmoro Ekawati Ellyta Ellyta Eviliyanto Eviliyanto, Eviliyanto Fera Fera Fitriani Dwi Susanti Florensia Rentia Florensia Rintia Francista Francista Francista Francista Galuh Bayuardi Hardi Dominikus Bancin Holifah Nurfitri Holifah Nurfitri Mohd Hairy Ibrahim Nurul Ramdhania Paiman Paiman Rahmatullah Rizieq Rika Angela Rosanti, Rosanti RR. Ella Evrita Hestiandari Rustam -, Rustam Sulha Wiwik Cahyaningrum Yoga Prasetya Adi Nugraha