Claim Missing Document
Check
Articles

Found 4 Documents
Search
Journal : geoeco

USING OF N-DIMENSIONAL EUCLIDEAN DISTANCE TO DETERMINE LOCATION WITH LACK OF HOSPITAL WITH HEALTH SOCIAL SECURITY AGENCY SERVICE Alif, Satrio Muhammad; Lestari, Mardiana Tri
GeoEco Vol 8, No 2 (2022): GeoEco July 2022
Publisher : Universitas Sebelas Maret (UNS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ge.v8i2.54577

Abstract

Health Social Security Agency or Badan Penyelenggara Jaminan Sosial Kesehatan (BPJSK) is a health to make people pays inexpensive price to get medical treatment. One of the shortcomings of BPJSK is regency of BPJSK card owner must be identical with the regency of target hospital. Lampung Province has varying location and uneven distribution of hospitals especially in regencies. This study aims to determine location with lack of hospital with BPJSK by using of n-dimensional Euclidean distance. The three-dimensional coordinate of 2098 sample points (SP) and 77 hospitals are the quantitative parameter used to calculate the distance. Every hospital and SP are assigned an identity number depending on the regency of each hospital and SP. Each SP pairs with its closest hospital. The SP with different identity is grouped. 32.1% of area of Lampung Province is the location with lack of hospital with BPJSK. The most prioritized regencies is Pringsewu Regency based on the distance and the population. Further research about spatial analyzing the exact location to build hospital with BPJSK service should be conducted.
DETERMINING THE LOCATION OF LAND SUBSIDENCE OBSERVATION POINTS BASED ON LITHOLOGICAL DATA AND LAND COVER CHANGES IN LAMPUNG PROVINCE Perdana, Redho Surya; Fikri, Muhammad; Alif, Satrio Muhammad; Isnaini, Een Lujainatul; Fauzi, Adam Irwansyah
GeoEco Vol 8, No 2 (2022): GeoEco July 2022
Publisher : Universitas Sebelas Maret (UNS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ge.v8i2.50412

Abstract

Land subsidence is a phenomenon that always occurs due to natural factors as well as human actions. Land subsidence has an even impact on all fronts. Land subsidence occurs continuously, therefore it is necessary to observe the phenomenon of land subsidence periodically using the GNSS method, which requires a benchmark that serves as a reference point for observation. With the need for a new benchmark devoted to observing land subsidence, it is necessary to do spatial modeling which is useful for finding out the suitability of the location where the subsidence observation point will be made. Spatial modeling was carried out using land cover data and lithology type to then be given weight and score and determined the soil movement vulnerability class into three, namely low class, medium class, and high class. The results of the spatial modeling of subsidence vulnerability show that the area12292.60 square kilometers is low grade, 20230.64 square kilometers represents medium class and 540.32 square kilometers is high class. Based on these results, the planning of the location of new observation points was carried out in areas with moderate to high levels of vulnerability with a total of 87 points scattered throughout the cities in Lampung.
COSEISMIC DEFORMATION OF THE 2020 BENGKULU MW 6.8 EARTHQUAKE USING INSAR DATA Ongky Anggara; Satrio Muhammad Alif
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.v11i1.90987

Abstract

An earthquake with a seismic moment magnitude of Mw 6.8 occurred in Bengkulu province, located on the southwestern coast of Sumatra, on August 18, 2020. This study aims to assess the application of the differential interferometric synthetic aperture radar (DInSAR) method to detect and analyze coseismic deformation due to this earthquake using the Sentinel-1A radar satellite. The results of the DInSAR did not yield significant coseismic signals with the range of Line of Sight (LOS) displacement of ~-40 mm to ~40 mm. The InSAR data did not detect clear deformation patterns or displacements associated with the August 18, 2020 earthquake. Further investigations are needed to understand the limitations of InSAR in detecting coseismic signals for this specific event. Integrating these datasets can provide a more comprehensive understanding of the earthquake source, fault characteristics, and associated deformation patterns.
RAPID MAGNITUDE ESTIMATION OF 2019 M6.9 BANTEN EARTHQUAKE USING GNSS 1HZ Ongky Anggara; Novia Rohmadona; Redho Surya Perdana; Satrio Muhammad Alif; Een Lujainatul Isnaini; Muhammad Al Kautsar
GeoEco Vol 12, No 2 (2026): GeoEco July 2026
Publisher : Universitas Sebelas Maret (UNS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ge.v12i2.109235

Abstract

Rapid magnitude estimation remains challenging in Indonesia due to the limited evaluation of high-rate Global Navigation Satellite System (GNSS) data and the lack of region-specific validation of existing Peak Ground Displacement (PGD) scaling relations for earthquake early warning applications. This study investigates the performance of high-rate GNSS data (1 Hz) for rapid magnitude estimation of the August 2 2019, Banten earthquake (Mw 6.9). Using 15 InaCORS stations provided by the Geospatial Information Agency of Indonesia, the data were processed using Precise Point Positioning with Ambiguity Resolution (PPP-AR). PGD values were extracted and applied to three empirical scaling relations proposed by Melgar et al. (2015), Crowell et al. (2016), and Ruhl et al. (2019). This study presents a comparative evaluation of multiple PGD scaling models using real Indonesian GNSS data, providing insight into their performance in a tectonic setting that remains underrepresented in previous studies. The results show that all models successfully converged to Mw 6.9, with convergence times ranging from 20 to 160 seconds after the earthquake origin time. However, this study is limited by the analysis of a single earthquake event and the use of global scaling relations that are not specifically calibrated for Indonesian tectonic conditions. These findings demonstrate the potential of high-rate GNSS as a complementary tool to seismic sensors for rapid magnitude estimation. The integration of GNSS into the Indonesia Tsunami Early Warning System (InaTEWS) is therefore recommended to improve the reliability and timeliness of earthquake and tsunami early warning.