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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.
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.
Zona Perlindungan Sumber Banyuning untuk Menjaga Keberlanjutan Air Tanah Kota Batu. Solikh, Mochammad Wildanun; Hendrayana, Heru; Budianta, Wawan
Majalah Geografi Indonesia Vol 40, No 1 (2026): Majalah Geografi Indonesia
Publisher : Fakultas Geografi, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/mgi.114478

Abstract

Abstrak Air tanah merupakan sumber daya penting yang menopang kebutuhan domestik, pertanian, dan aktivitas ekonomi, namun tekanan terhadap keberlanjutannya semakin meningkat akibat perubahan penggunaan lahan dan pertumbuhan penduduk. Kota Batu sebagai wilayah hulu Daerah Aliran Sungai Brantas memiliki banyak mata air yang bergantung pada sistem akuifer vulkanik, salah satunya Sumber Banyuning yang dimanfaatkan secara intensif oleh masyarakat. Penelitian ini bertujuan untuk mengkaji kondisi geologi dan hidrogeologi serta menentukan zona perlindungan Mata Air Sumber Banyuning sebagai dasar pengelolaan sumber daya air tanah yang berkelanjutan. Penentuan zona perlindungan dilakukan melalui metode zonasi mata air yaitu hidrogeologi, manual, solusi analitik, serta kombinasi ketiga metode tersebut. Hasil penelitian menunjukkan bahwa wilayah penelitian tersusun atas tiga satuan litologi utama yaitu andesit Anjasmoro, andesit Arjuno Welirang, dan breksi gunung api Arjuno Welirang. Aliran air tanah bergerak dari barat laut menuju tenggara mengikuti kemiringan topografi sehingga daerah imbuhan berada di bagian barat laut. Berdasarkan analisis tersebut ditetapkan empat zona perlindungan, yaitu Zona I dengan radius 10 m dan luas 121 m2, Zona II dengan radius sekitar 336 m dan luas 0,136 km2, Zona III dengan radius sekitar 2,56 km dan luas 4,24 km2, serta Zona Imbuhan dengan luas minimal 5,63 km2 yang terletak hingga sekitar 4,32 km dari mata air. Analisis penggunaan lahan menunjukkan bahwa zona perlindungan didominasi oleh hutan, lahan perkebunan, dan sebagian permukiman yang berpotensi memengaruhi proses infiltrasi dan kualitas air tanah. Oleh karena itu, pengelolaan dilakukan melalui pengaturan aktivitas pada setiap zona, yaitu perlindungan ketat di Zona I, pembatasan penggunaan bahan kimia dan penanaman vegetasi pada Zona II, pengendalian aktivitas pencemar pada Zona III, serta pelestarian tutupan hutan pada zona imbuhan. Penetapan zonasi ini diharapkan dapat mendukung konservasi air tanah dan menjaga keberlanjutan Mata Air Sumber Banyuning di Kota Batu.Abstract Groundwater is an important resource that supports domestic, agricultural, and economic activities; however, increasing pressure on its sustainability has emerged due to land use change and population growth. Batu City, located in the upstream area of the Brantas River Basin, contains numerous springs associated with volcanic aquifer systems, one of which is Banyuning Spring that is intensively utilized by local communities. This study aims to examine the geological and hydrogeological conditions and to determine the protection zones of Banyuning Spring as a basis for sustainable groundwater resource management. The delineation of spring protection zones was conducted using a spring zoning approach including hydrogeological analysis, manual methods, analytical solutions, and a combination of these approaches. The results show that the study area consists of three main lithological units, namely Anjasmoro andesite, Arjuno–Welirang andesite, and Arjuno–Welirang volcanic breccia. Groundwater flow moves from northwest to southeast following the regional topographic gradient, indicating that the recharge area is located in the northwestern part of the study area. Based on this analysis, four protection zones were established, namely Zone I with a radius of 10 m and an area of 121 m2, Zone II with a radius of approximately 336 m and an area of 0.136 km2, Zone III extending about 2.56 km with an area of 4.24 km2, and a recharge zone with a minimum area of 5.63 km2 located up to approximately 4.32 km from the spring. Land use analysis indicates that the protection zones are dominated by forest, plantation areas, and limited settlements that may influence infiltration processes and groundwater quality. Therefore, management strategies are implemented by regulating activities in each zone, including strict protection in Zone I, restriction of chemical use and vegetation planting in Zone II, control of potential contaminating activities in Zone III, and preservation of forest cover within the recharge zone. The delineation of these zones is expected to support groundwater conservation and maintain the sustainability of Banyuning Spring in Batu City.Submitted:2025-12-17 Revisions:2026-03-02 Accepted:2026-03-09 Published:2026-03-10