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Journal of Applied Geology
Published by Universitas Gadjah Mada
ISSN : 25022822     EISSN : 25022822     DOI : https://doi.org/10.22146
Core Subject : Science, Social, Engineering,
Civil Engineering, Building, Construction & Architecture Earth & Planetary Sciences Energy Engineering Environmental Science
Journal of Applied Geology – JAG focuses on the applied geology and geosciences with its key objective particularly emphasis on application of basic geological knowledge for addressing environmental, engineering, and geo-hazards problems. The subject covers variety of topics including geodynamics, sedimentology and stratigraphy, volcanology, engineering geology, environmental geology, hydrogeology, geo-hazard and mitigation, mineral resources, energy resources, medical geology, geo-archaeology, as well as applied geophysics and geodesy.
Arjuna Subject : Ilmu Bumi dan Planet (semua kategori) - Geologi
Articles 3 Documents
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Search results for , issue "Vol 10, No 1 (2025)" : 3 Documents clear
Excavation Method of Rock Masses at the Matenggeng Dam, Indonesia Afandi, Valentino Ilham; Indrawan, I Gde Budi; Husein, Salahuddin
Journal of Applied Geology Vol 10, No 1 (2025)
Publisher : Geological Engineering Department Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jag.103735

Abstract

This paper presents the results of engineering geological investigations and determination of rock mass excavation methods in the main dam area of Matenggeng Dam. The study was carried out through engineering geological mapping, core drill evaluation and supported by laboratory test data. Classifications of rock masses were carried out based on the Geological Strength Index (GSI) and Rock Mass Rating (RMR) to analyze the excavation method. The results showed research area consisted of lithology in the form of andesite, intercalation sandstone - gravelly sandstone unit, intercalation sandstone - siltstone unit, and alluvium deposits. However, at the main dam area consists of lithology in the form of intercalation sandstone-siltstone unit and intercalation sandstone-gravelly sandstone unit. The rock masses at the main dam excavation line have a weathering degree from moderately to complately weathered. Intact rocks have Uniaxial Compressive Strength (UCS) values ranging from 1-50 Mpa and are a category of extremly weak to moderate rocks. The rock mass of intercalation sandstone-siltstone with very poor to poor quality (GSI (0 - 58), RMR (8 - 45)), and intercalation sandstone-gravelly sandstone with poor to fair quality (GSI (20 - 59), RMR (20 - 68)). The recommended rock excavation method based on the EXCASS System is diggir, easy ripper, and hard ripper.
Improving Landslide Susceptibility Using Groundwater Parameter in Samigaluh and Kalibawang Subdistricts Susatio, Raja; Sartohadi, Junun; Samodra, Guruh; Setiawan, Muhammad Anggri; Wilopo, Wahyu
Journal of Applied Geology Vol 10, No 1 (2025)
Publisher : Geological Engineering Department Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jag.106054

Abstract

Landslide susceptibility map is crucial in disaster risk management and it can be used for regional development plans. Landslide susceptibility map can be made by analyzing parameters that are assumed to affect landslides such as gradient slopes, geology, soil, and climate. Selection of landslide controlling parameters influences the accuracy of landslide susceptibility map. This study evaluates the effect of parameter that’s rarely used which is groundwater. The study area of this research was Kalibawang and Samigaluh Subdistricts, Kulonprogo, Special Region of Yogyakarta, Indonesia. Frequency ratio was used for the method along other parameters which is slope gradient, lithology, lineament density, land use, soil thickness. The result shows that groundwater parameter increase the accuracy by 22,29%. This study suggest that groundwater should be highly considered in landslide susceptibility mapping. In the other hand, groundwater depth mapping remains a challenge because most remote sensing method only detect shallow groundwater. Further research is necessary to develop better method for groundwater mapping using remote sensing or other indirect method.
Unsupervised Machine Learning for Determining Exploration Areas of Valuable Elements and Potential Toxicology Elements: A Case Study of the Bowen Basin Coal, Australia Addintamma, Fajri Zakka; Amaranggana, Adzani Nareswari; Kusuma, Anindya Ayu; Aviliana, Aviliana; Solikh, Mochammad Wildanun; Patria, Aulia Agus; Anggara, Ferian
Journal of Applied Geology Vol 10, No 1 (2025)
Publisher : Geological Engineering Department Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jag.104595

Abstract

Global coal production and demand have increased anually. In addition to its potential as an alternative source of critical elements, coal also has environmental risks through toxicology elements. Australia is the world’s second-largest producer of rare earth elements (REEs) and critical elements, making coal exploration a key focus of the country’s mining strategy. An unsupervised Machine learning algorithm was applied to 56 coal samples from three pits in Bowen Basin, e.g., Blake Central Pit, Blake West Pit, and Bowen No. 2 Pit, to correlate trace elements with the geochemical characteristics of coal, such as proximate and major oxides. Blake West Pit is enriched in Ba, Br, and Sr, which associated with inherent moisture and phosphor (P), extending SE-trend. Blake Central Pit and Blake West Pit are enriched in Hf, Mo, Ta, Th, Y, and REY, which are associated with ash and major elements such as Si, Al, Ti, and K, with a trend of potential exploration towards N-NW. However, both pits show the risk of contamination from the toxic element Zn, which is associated with volatile matter, and major elements e.g., Fe, Mg, and Mn, with a trend of distribution towards S-SW. Based on the correlation analysis and regional geology, trace element enrichment in Bowen Basin is controlled by two main factors: 1) the transgressive phase during Early-Late Permian, which enriched inherent moisture, P, Ba, Br, and Sr, and 2) volcanic activity during Early Permian, which enriched silicate minerals and elements such as Hf, Ta, Th, W, and REY. Unsupervised machine learning has proven effective for preliminary coal characterization to support further exploration.

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