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"ABSTRAKTelah dilakukan penelitian untuk identifikasi ketebalan lapisan lapuk yang berada di atas lapisan batuan vulkanik yang menghambat proses eksplorasi hidrokarbon di Kabupaten Majalengka menggunakan metode HVSR Mikrotremor. Potensi reservoir hidrokarbon diperkirakan pada lapisan batuan sedimen pada Formasi Cinambo di bawah lapisan batuan vulkanik Praptisih dan Kamtono, 2016 . Potensi hidrokarbon dibuktikan dengan kemunculan rembesan minyak pada sebelah utara dari area penelitian. Hasil survey seismik aktif menunjukkan kualitas yang tidak memuaskan akibat lapisan batuan vulkanik yang menghalangi penjalaran gelombang. Penelitian dilakukan untuk memperkuat hasil penelitian sebelumnya dan mengetahui ketebalan lapisan lapuk di atas lapisan batuan vulkanik. HVSR Mikrotremor merupakan metode yang mampu mendeteksi ketebalan lapisan dengan memanfaatkan gelombang permukaan. Pengukuran dilakukan pada area seluas 15 km2 dengan lama waktu pengukuran selama 1 - 2 jam di tiap titik. Peralatan yang digunakan adalah digital seismometer short period dengan 3-Komponen. Rasio H/V Horizontal to Vertical Spectral Ratio menunjukkan hubungan antara nilai frekuensi natural dengan ketebalan lapisan lapuk. Ketebalan lapisan lapuk dihitung dengan rumusan dari Bard 2000 . Dilakukan pula inversi data dan pemodelan 2D/3D menggunakan model kecepatan untuk menunjukkan ketebalan lapisan lapuk melalui nilai kecepatan. Penelitian diharapkan mampu menunjukkan respon frekuensi pada lapisan lapuk di atas lapisan batuan vulkanik.

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ABSTRAKThe research have been conducted for identifying the thickness of weathered layer over volcanic rock layer that prohibit the hydrocarbon exploration in Majalengka District, Indonesia by using HVSR Mikrotremor method. The potential reservoir is expected on sedimentary rock of Cinambo Formation below the volcanic layer Praptisih and Kamtono, 2016 . The hydrocarbon potential are proven by the presence of oil seepage in the northern side of research area. Active sesimic survey showed unsatisfactory results because the volcanic layer has scaterred the seismic wave propagation. This study aims to strengthen the previous results and to determine the thickness of weathered layer over volcanic rock layer. HVSR Microtremor is a method that can detect the thickness of layer by utilizing surface wave. Measurements carried out on an area of 15 km square with acquisition time around 1 2 hours for each station. The equipment is a digital short period seismometer with 3 axis components. The horizontal to vertical spectral ratio H V Spectral Ratio showed that the natural frequency signal can correlate to the thickness of volcanic rock layer. The thickness of weathered layer have been estimated using the Bard 2000 equation about the relation of natural frequency and the thickness of bedrock. A data inversion and 2D 3D modelling has been performed by using velocity model to show the thickness of weathered layer through a velocity value. This research is expected to show the response of the frequency of the weathered layer over volcanic rock layer."

"Klasifikasi tipe gunungapi di Indonesia dibagi menjadi tiga berdasarkan sejarah letusannya, yaitu tipe A, B , dan C. Lokasi penelitian merupakan Gunung Karang, Kabupaten Pandeglang, Provinsi Banten yang merupakan gunungapi tipe B. Selain itu, ditambahkan gunungapi tipe A untuk melihat perbedaan penggunaan metode, yaitu Gunung Raung, Kabupaten Banyuwangi, Kabupaten Bondowoso, dan Kabupaten Lumajang, Provinsi Jawa Timur. Lalu, untuk melihat perubahan deformasi pada gunung tersebut dari tahun 2015 hingga 2020 digunakan metode Interferometric Synthetic Aperture Radar (InSAR). Hasil dari pengolahan data dengan menggunakan teknik InSAR menunjukan bahwa di Gunung Karang dari tahun 2015 hingga 2020 tidak menunjukan adanya deformasi yang terbentuk. Teknik ini akan lebih baik digunakan pada daerah yang minim vegetasi, karna citra interferogram yang terbentuk tidak akan menunjukan informasi jika digunakan pada daerah yang memiliki vegetasi yang tinggi.

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Classification of volcanic types in Indonesia is divided into three based on the history of eruptions, namely types A, B, and C. The research location is Mount Karang, Pandeglang Regency, Banten Province which is a type B volcano. In addition, type A volcano is added to see the differences in the use of the method, namely Mount Raung, Banyuwangi Regency, Bondowoso Regency, and Lumajang Regency, East Java Province. Then, to see changes in deformation on the mountain from 2015 to 2020, the method was used Interferometric Synthetic Aperture Radar (InSAR). The results of data processing using the technique InSAR show that at Mount Karang from 2015 to 2020 there is no deformation formed. This technique would be better used in areas with minimal vegetation, because the formed interferogram image will not show information if used in areas with high vegetation."

"The result of my previous study in alluvial deposits areas (Kabupaten Subang, West Java) has shown the high concentration of nitrogen compounds (ammonium and nitrate) on shallow groundwater. While the presence of nitrogen compounds on groundwater will cause negative impact, especially for human health and water ecosystem. The research project is important to be done, because the permeability of aquifer layer in the research areas {young volcanic deposits) was higher than the alluvial deposits areas. More than 80 percent population in the research areas uses shallow groundwater and springs. They utilized without treatment, while the capability of Municipal Water Corporation to meet their needs is very limited."

"ABSTRAKIdentifikasi keberadaan debu vulkanik dan prediksi sebarannya di udara pada saat terjadi erupsi gunung berapi sangat diperlukan guna keselamatan penerbangan dan publik secara umum. Berbagai metode telah dikembangkan untuk keperluan pemantauan sebaran debu agar dapat memberikan peringatan dini kepada pemangku kepentingan yang terkait. Penelitian ini dilakukan untuk memperoleh informasi tentang perbedaan sebaran debu vulkanik dengan tiga metode deteksi yang berbeda dan membandingkan hasil prediksi model HYPSLITdan observasi sebaran debu vulkanik dengan citra satelit cuaca MTSAT/Himawari.Kasus erupsi gunung yang dikaji berbeda baik tipe erupsi maupun waktu kejadian khususnya pada kasus erupsi Gunung Kelud 13-14 Februari 2015, Gunung Rinjani 16 Juli 2015, dan Gunung Rinjani 3-4 November 2015. Hasil penelitian menunjukkan bahwa terdapat perbedaan pola sebaran debu vulkanik antara tipe erupsi yang berbeda yang disebabkan oleh beberapa faktor antara lain: ketinggian kolom erupsi, volume material vulkanik, arah dan kecepatan angin pada beberapa ketinggian atmosfer. Prediksi sebaran debu vulkanik Gunung Kelud dengan model HYSPLIT memiliki indeks kesamaan yang cukup tinggi dengan hasil observasi satelit, dengan nilai Indeks Similaritas sebesar 59.68 . Sedangkan indeks similaritas untuk G. Raung dan G. Rinjani relatif kecil yaitu sebesar masing-masing 17.96 dan 15.97 .

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ABSTRACTIdentification of the presence of volcanic ash and distribution forecast in the air during a volcanic eruption is very important to flight safety and the general public. Various methods have been developed to monitor the distribution of volcanic ash in order to provide early warnings to the relevant stakeholders. This research was conducted to obtain information about the differences in the distribution of volcanic ash with three different detection methods and comparing the results of HYPSLIT model predictions of volcanic ash dispersion with observation by MTSAT Himawari weather satellite imageries. Different types of eruptions and time of occurrence were examined Mt. Kelud eruption on 13 to 14 February 2015, Mt. Rinjani eruption on 16 July 2015, and Mt. Rinjani eruption on 3 4 November 2015. The results showed that there were differences between the distribution patterns of volcanic ash eruption between different eruption types which were caused by several factors such as height of the eruption column, the volume of volcanic material, wind speed and direction at some altitude atmosphere. Prediction of volcanic ash distribution for Mt. Kelud with HYSPLIT model resulting moderate similarity compared to the results of satellite observations, with the value of Jaccard Similarity Index of 59.68 . Whereas for both Mt. Raung and Mt. Rinjani shown relatively weak similarity index values of 17.96 and 15.97 respectively. "

"Debu vulkanik merupakan partikel yang sangat berbahaya bagi aktivitas penerbangan. Objek tersebut dapat diamati secara spasial melalui pengamatan satelit. 8. Namun, satelit ini memiliki kelemahan berupa pergeseran akibat kesalahan sudut baca ketika objek yang diamati jauh dari posisi nadir satelit. Data target output debu vulkanik yang digunakan merupakan hasil interpretasi forecaster berdasarkan pengamatan satelit Terra/Aqua (MODIS) yang memiliki orbit polar sehingga pengamatan dilakukan tepat diatas objek. Algoritma sampel yang dilakukan untuk membuat model adalah dengan variasi sampel berupa data piksel tunggal dan data rata-rata piksel pada citra satelit Himawari Untuk menentukan lokasi debu vulkanik berdasarkan citra satelit, dibutuhkan interpretasi dari forecaster. Pada penelitian ini, dibuat sebuah sistem pemodelan berbasis artificial neural network untuk menghasilkan output sebaran debu vulkanik secara otomatis berdasarkan training data dari citra satelit Himawari 8. Namun, satelit ini memiliki kelemahan berupa pergeseran akibat kesalahan sudut baca ketika objek yang diamati jauh dari posisi nadir satelit. Data target output debu vulkanik yang digunakan merupakan hasil interpretasi forecaster berdasarkan pengamatan satelit Terra Aqua (MODIS) yang memiliki orbit polar sehingga pengamatan dilakukan tepat diatas objek. Algoritma sampel yang dilakukan untuk membuat model adalah dengan variasi sampel berupa data piksel tunggal dan data rata-rata piksel pada citra satelit Himawari Sedangkan variasi data input yang digunakan terdiri dari 3 input, 16 input, dan 4 input kanal satelit. Metode pengujian performa dari model dilakukan dengan melihat citra sebaran debu yang dihasilkan model yang diverifikasi di setiap titik piksel. Berdasarkan hasil penelitian, model dengan menggunakan 3 input kanal satelit dapat mendeteksi sebaran debu vulkanik dengan baik pada data training maupun testing. Untuk koreksi kesalahan paralaks satelit Himawari memiliki dampak yang cukup signifikan terhadap hasil output model. Akurasi dari output model meningkat signifikan setelah dilakukan koreksi spasial akibat kesalahan paralaks yang menghasilkan akurasi model pada saat testing mencapai 95 persen "

"Mount Merapi in Central Java is one of the world’s most studied volcanoes. The frequent eruptions of this volcano and the densely populated areas on its slopes make Merapi particularly important to scholars of the natural and social sciences. Considerable attention has been devoted to contemporary aspects of this volcano, including research into forecasting and monitoring possible volcanic activity and eruptions. However, research investigating artistic representations of Merapi in a historical context, particularly local artworks referring to how people responded to a natural hazard such as a volcanic eruption, is still rare. In this paper, I explore how artists in the period 1800-1930 have portrayed the volcanic activities in their drawings and paintings. Various historical data, including newspapers, reports, and records of volcanic eruptions, will be used to help interpret the accuracy of the paintings which depict Merapi at different moments in time. I argue that artists in the period under investigation were acutely aware of Merapi’s volcanic activities and depicted these in their drawings and paintings, because of the influence of science, which invokes interest in Merapi, landscape art, and a sense of humanitarianism. Their artworks are dynamic visual historical reflections of Merapi which testify to the power and beauty of nature."

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ABSTRACTThis textbook provides a modern, quantitative and process-oriented approach to equip students with the tools to understand geomorphology. Insight into the interpretation of landscapes is developed from basic principles and simple models, and by stepping through the equations that capture the essence of the mechanics and chemistry of landscapes. Boxed worked examples and real-world applications bring the subject to life for students, allowing them to apply the theory to their own experience. The book covers cutting edge topics, including the revolutionary cosmogenic nuclide dating methods and modeling, highlights links to other Earth sciences through up-to-date summaries of current research, and illustrates the importance of geomorphology in understanding environmental changes. Setting up problems as a conservation of mass, ice, soil, or heat, this book arms students with tools to fully explore processes, understand landscapes, and to participate in this rapidly evolving field."