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–– Tambang Sawah Area, Lebong Regency, Bengkulu Province, is geologically located in the Barisan mountains and Sumatra fault zone. The prospect of Tambang Sawah area lies in the physiography of the central Sumatran mountains ranges composed by the igneous rocks of the Sunda – Banda magmatic arc. This study is aimed to understand the deposit geology and ore characteristics of the gold deposit at the study area. Quartz vein mineralization of Tambang Sawah occurred in granite rock intruded into andesitic breccia rocks, with the geological structure of mineralization control in the form of joint, breccia, dike, and fault, namely the Ketahun fault that forms extentional fracture zones which were filled by hydrothermal fluid in form of quartz veins. Hydrothermal alterations that appear at the study site are typical types of alterations found in epithermal gold deposits, namely, argillic, silicified and propylitic. Sulfide minerals markers of low sulfidation epithermal type gold deposits found, namely, pyrite, calcopyrite, covelite, sphalerite and galena with colloform vein texture, cockade-crustiform, moss, and brecciated texture. Gold is interpreted to be derived from the deposition of sulfide minerals and the deposition of quartz veins, the level of gold in rocks and veins varies greatly with an average 4,8 ppm. Based on the results of ore geochemical analysis of positively correlated gold with elements Ag, Cu, Pb and Zn. Keywords: Mineralization, low sulfidation epithermal gold, Tambang Sawah, Lebong, Bengkulu.

Accurate satellite precipitation estimates over areas of complex topography are still challenging, while such accuracy is of importance to the adoption of satellite data for hydrological applications. This study evaluated the ability of Integrated Multi-satellitE Retrievals for GPM -Final (IMERG) V06 product to observe the extreme rainfall over a mountainous area of Sumatra Island. Fifteen years of optical rain gauge (ORG) observation at Kototabang, West Sumatra, Indonesia (100.32°E, 0.20°S, 865 m above sea level), were used as reference surface measurement. The performance of IMERG-F was evaluated using 13 extreme rain indexes formulated by the Expert Team on Climate Change Detection and Indices (ETCCDI). The IMERG-F overestimated the values of all precipitation amount-based indices (PRCPTOT, R85P, R95P, and R99P), three precipitation frequency-based indices (R1mm, R10mm, R20mm), one precipitation duration-based indices (CWD), and one precipitation intensity-based indices (RX5day). Furthermore, the IMERG-F underestimated the values of precipitation frequency-based indices (R50mm), one precipitation duration-based indices (CDD), one precipitation intensity-based indices (SDII). In terms of correlation, only five indexes have a correlation coefficient (R) > 0.5, consistent with Kling–Gupta Efficiency (KGE) value. These results confirm the need to improve the accuracy of the IMERG-F data in mountainous areas.

Long-term InSAR-based observations are prone to atmospheric delay interference. The active-phase signals emitted and recorded back by sensors during imaging are easily disturbed by the electron content in the ionospheric layer and the water vapor content in the tropospheric layer. Given that the short wavelength of the C-band used by Sentinel-1 is more sensitive to tropospheric delay than to ionospheric delay, in this work, we utilized InSAR Sentinel-1 data to observe the postseismic deformation that occurred following the 2018 Palu earthquake and to evaluate the effect of tropospheric delay on the estimated interferogram time series. The cloud computation of Looking into Continent from Space with Synthetic Aperture Radar (LiCSAR) and LiCSBAS was used to generate interferograms and analyze the time series. Here the atmospheric delay was modeled by using Generic Atmospheric Correction Online Service (GACOS) and removed from the generated interferograms. Results showed that the annual velocity and cumulative line-of-sight (LOS) displacement were refined by correcting the atmospheric delay. Specifically, by applying GACOS, the standard deviation of the generated interferograms decreased by up to 76.6%. GNSS observations were utilized to verify the improvement due to the removal of tropospheric noise. We found that LOS displacement with GACOS correction better fitted the GNSS observation than LOS displacement without GACOS correction. Therefore, atmospheric correction plays an important role in long-term InSAR-based observations, especially in avoiding any bias in the interpretation of the estimated time series.

The mathematical modelling of geological structures, i.e. magma intrusion or dyke, has been done, based on magnetic data with inversion techniques using MatLab. The magnetic equation is a non-linear equation, and completion is done using a linear approach to non-linear mathematical models of magnetic data using the Taylor expansion approach and Jacobi Matrix. The first step of this research is to make synthetic data forward modelling from the magnetic equation of magma intrusion or dyke cases without errors, and the next stepping then add errors to the data. The next step is to do an inversion to get the parameters sought, i.e. depth and angle of the magma intrusion, by giving initial guesses, and then re-correct iteratively until convergent results are obtained. Finally, parameters of slope dyke or thin magma intrusion and its depth can be determined. The results obtained indicate that this technique can be used to get physical parameters sought from magnetic data for simple geological cases, i.e. dyke and magma intrusion.

This paper describes the effect of parameter variation with Kirchhoff migration in post-stack seismic data. Parameters tested covering velocity, aperture, and maximum dip. The data used in this work was generated from velocity and density models with gaussian syncline and anticline layer boundaries. This work is the effect of parameter changes on the model and conclude best applied parameters for Kirchhoff migration in certain model created.

The microseismic method is relatively new in groundwater exploration, especially in Indonesia. This study will examine the response of microseismic to groundwater aquifer systems. This study aims to analyze the response of seismic waves and to interpret the seismic wave response characteristics to the aquifer system model. The modeling of the aquifer system was carried out using seismic stratigraphy data. This data was used as input data to model the exposed HVSR curve using the Microtrem program in MATLAB. The study of physical parameters and supporting parameters of the aquifer layer and the air contained in it was carried out to support this modeling. The aquifer system modeling was carried out with various parameters, including saturation, porosity, and thickness of the aquifer layer. Furthermore, an analysis of the model is carried out to determine the response characteristics of the aquifer system to microseismic waves. The results show that the frequency range as a marker of the presence of the aquifer ranges from 2-4 Hz, which is determined by parameters within a specific value.

Accurate information on extreme rain is essential for vulnerability analysis and early warning systems of hydrometeorological disasters. One newly launched satellite that can provide information about extreme precipitation is the Global Precipitation Measurement (GPM), which produces half-hour grid data through the Integrated Multi-Satellite Retrieval for GPM (IMERG) system. This work evaluates the performance of IMERG data to measure extreme precipitation indices over Indonesia. Three types of GPM IMERG data: IMERG-Early, IMERG-Late, and IMERG-Final, were validated by rain gauge data in Indonesia for extreme rain indices from 2016 to 2019. Overestimated values for extreme precipitation indices were dominated by low-intensity precipitation such as PRCPTOT, R1mm, and CDD indices. On the contrary, underestimated values of extreme precipitation indices dominated by high-intensity precipitation such as R90p, R95p, R50mm, and RX1day indices. Moreover, the different types of IMERG data showed a similar pattern with slightly different values for identifying extreme precipitation indices. Thus, a more comprehensive study is needed to improve GPM IMERG in observing the extreme precipitation over Indonesia.

The Earth's crust layer and sediment in Western Indonesia has been studied using the inversion of teleseismic receiver function from BMKG’s seismic network. Earthquake events were analyzed in this study with a moment magnitude greater than 6.0 with epicentral distances of 30° to 90°. A total of 60 earthquake events were observed and recorded by 91 stations around the study area. Furthermore, an inversion process was carried out using the initial velocity model from the modification of the AK135f velocity model to obtain the shear wave velocity structure below each stations. The velocity model from the azimuthally stacked vertical receiver function showed that the sediment layer had a relatively medium shear wave velocity value with an average of 2.1 km/s, while the crust layer had 4.60 km/s. The sedimentary layer thickness in this region also varies between 2 km to 10 km. A relatively thick sediment layer of about 8 km to 10 km was observed in two locations, in East Kalimantan associated with the Kutai Basin and Northern part of Sumatera in the North Sumatera Basin, a two major oil producer basinal area in Indonesia. The Moho discontinuity was also found at depths that vary between 16 km to 50 km. In addition, the most shallow Moho depth is 16 km below the North Kalimantan and North part of West Java, while the deeper Moho depth of 50 km is located below East Kalimantan, Central Kalimantan, North Sumatera and South Sumatera.

Kelud is one of Indonesian volcano lies between Kediri and Blitar districts of East Java province. This volcano has erupted since 1000 where casualties of 200000 people emerged until the last eruption in 2014. Therefore, it is needed a volcano early warning system to detect the eruption earlier for minimizing the casualties. We have developed an early warning system based on sensor nodes consist of vibration, temperature and gasses (sulfur and carbon dioxide) sensors to monitor the physical parameter of the volcano, drone surveillance, mapping and temperature measurement, and mobile robot consists of the same sensor as in the node for both normal and emergency situations. The system has been tested in Kelud volcano in August 2019. In a normal condition, the system has detected 1 Hz of seismicity, under 1 ppm of sulfur and carbon dioxide, 23-55.3oC of the lake temperature, 32oC of the ground temperature and 23-25oC of the air temperature. The system could be used for 37 hours of full operation for 1 charging cycles of solar cell’s charging process where suitable for dangerous environment application.

Eastern Indonesia is tectonically complex, formed by different plates and microplates interactions from different origins. This complexity gives geoscientists a challenge to solve the ’jigsaw’ of the complex interactions. The understanding of tectonic processes can lead to a breakthrough in both resource exploration and disaster risk reduction. We utilize teleseismic P wave coda for random coda from scattering and deterministic coda originated from the crust-mantle boundary (Moho) to derive the crustal properties, including thickness, Vp/Vs, and qualitative scattering characteristics. For the scattering properties, we apply Iterative Cross-Correlation and Stacking (ICCS) to align the waveform. At the same time, for the crust characteristic, we employ the Receiver Functions (RF) method alongside H-k stacking. The crustal thickness recovered from the RF and H-k stacking has a good correlation with the crustal origin, where the thickness in older and stable crust originated from Sundaland and Gondwana is thicker than a younger plate of the crust arc and subduction origin. The Vp/Vs is high in a region that is interpreted to be dominated by mafic lower crust originated from oceanic-oceanic subduction during Eocene, anisotropy, or by a magmatic anomaly. The P coda also correlated well with the subsurface magmatic anomaly by providing a unique pattern.

The complexity of a system recorded in time series data can be measured statistically using permutation entropy (PE). The state of a system (e.g. regular, chaotic, random, etc.) that underlies the appearance of variations in time series can be determined with PE. Since volcanoes are considered as the complex dynamical system controlled by interactions of many processes. Permutation entropy can be applied to study the system mechanism of volcano. We utilized PE to study system mechanism of Kelud volcano in 2007 dome-forming eruption period, from 3 (KWH; KLD; UMBK) seismic stations with different distances from the crater lake. Then, we want to compare the results. The result of study shows that the PE pattern for each station is different. The unique PE pattern that can be used as an eruption precursor is only shown at KWH and KLD stations. This pattern began to appear 2.7 days before the eruption on 3 November 2007. Data from UMBK station doesn’t show unique PE pattern. The factors such as sensor distance from magmatic activity center, size, and type of eruption probably influenced the final PE result. Using PE as the addition to volcano monitoring can maximize efforts in mitigation activities.

Topography of a volcano crater can change due to endogenic processes such as deformation or eruption, or surface processes. Erosion and deposition are surface processes that may occur and gradually change the slope of the inner volcano crater. Here, we investigated erosion and deposition processes that occurred in the Kelud crater after the 2014 plinian eruption. We used high-resolution Digital Elevation Models (DEMs) and orthomosaic images derived by drone photogrammetry that acquired between September 2018 and July 2019. We obtained hundreds of aerial images which were reconstructed to obtain 3D models of Kelud’s crater by using Structure from Motion (SfM) technique. Results show erosions at alluvial fans that dominantly located at the east valleys of Kelud crater. The erosion removed the volcanic materials up to -5 m which transported and deposited close to the vicinity of the Kelud crater. The deposition process causes the increase of the Kelud crater lake up to 3 m. Moreover, we also mapped the thermal distribution of the Kelud crater lake by using low cost thermal camera. Our thermal investigation is able to identify some hotspots at the vicinity of the Kelud crater lake with range temperature of 43.7°C – 55.3°C, while the average apparent temperature of the Kelud crater lake is ~ 29°C. This high temperature area may indicate underwater active fractures that continuously release volcanic gasses which leads to convection heat transfer through Kelud’s water lake.

Information about the eruption of Mount Lawu in Central Java Province in 1885 and Mount Merapi in D.I. Yogyakarta in 2010 became a source for estimating the presence of magnetic minerals which underwent a sedimentation process in the Bengawan Solo River from upstream (Wonogiri) - downstream (Bojonegoro). The results we get of the magnetic susceptibility distribution of the Bengawan Solo sediments reveal that the sediment from the upper reaches of the Bengawan Solo River has a low frequency magnetic susceptibility value in upstream of around 1,080.23×10−8 m3/Kg - 2,780.77×10−8 m3/Kg, the middle part is 74.40×10−8 m3/Kg - 1,735.90×10−8 m3/Kg, and downstream 17.57×10−8 m3/Kg - 1,620.53×10−8 m3/Kg. The value of magnetic susceptibility decreased significantly from upstream to downstream. High susceptibility indicates the sample contains metal elements. In determining iron oxide, we use X-Ray Fluorescence assisted by X-Ray Diffractometer testing to determine magnetic minerals. X-Ray Fluorescence confirm metal oxide in the sample. There are Al and Fe confirm the presence of magnetic properties in sedimentation. The Vibrating Sample Magnetometer confirmed that the Bengawan Solo sediment has a magnetic saturation about 0.06 - 9.50 (emu/g), a magnetic remanent around 0.001 - 0.575 (emu/g) and coercivity field of around 10 - 60.15 (Oe). X-Ray Diffractometer pattern confirm the mineral structures, namely Coesite, Magnetite, Cristobalite, Portlandite, Quartz, Anatase, Goethite, Tridymite, Gibsyte, Stishovite, Grasullaria, Labradorite and Wuestite. These results indicate the novelty of sediments from Bengawan Solo, Central Java to East Java. HIGHLIGHTS We found several important points in this research: The Bengawan Solo River is formed from several formations and lifting from faults The Bengawan Solo River is rich in minerals formed from metal oxides The magnetic value decreases with the distance from Mount Lawu The Bengawan Solo River has confirmed ferromagnetic properties from the S-type hysterisis curve With low magnetic remanent values, low saturation magnetism and high magnetic corrosivity GRAPHICAL ABSTRACT

We present the combination of permutation entropy (PE) and power spectral density (PSD) analysis on continuous seismic data recorded by short-period seismic stations during the 2010 Merapi volcano eruption. The calculation of PE aims at characterizing the randomness level in seismic noise, while the PSD parameters use to detect the background noise level in various frequency bands. It was previously observed that a significant reduction of randomness before the volcano eruption could be indicated as one of the short-term precursors due to the lack of high frequencies (>1 Hz) in the noise wave-field caused by high absorption losses as the hot magma uprises to the upper crust. The results show no significant reduction in signal randomness before the eruption series. The characteristic of events during the preeruptive period and the crisis tends to be chaotic (PE in the range 0.9 to 1). Further calculations show that the standard deviation in PE decreased in four days before the first eruption onset on 26 October. PE was stable at the highest values (very close to 1) and gradually returned to the previous fluctuation after the eruption onset. The level of background noise in the low- and high-frequency bands appeared to have the same tendency. The two main eruptions correspond to the two highest peaks of noise levels.

Mt. Lamongan, East Java is located at near three major towns around, i.e. Probolinggo, Lumajang, and Jember. Its Mountain indicated saving the potential of geothermal energy. That seems from the existence of geothermal manifestations such as hot springs in Tiris Probolinggo. The hot spring temperature value at the surface is 67°C. Estimation of subsurface temperature distribution, model and the orientation of existing faults are very important to know, to the planning of geothermal exploitation. In this study, we used magnetic and gravity field anomaly data to approximate it. We use Mag3D and Grav3D software from the University of British Columbia (UBC) to make a 3D inversion of magnetic and gravity field data. The inversion is shown the pattern of subsurface susceptibility values and rock density clearly. The susceptibility values correlated with the presence of sub-surface heat source and the rock density is associated with the structural condition, i.e. model and orientation of fault in this area. In this study, we found the subsurface temperature distribution connected with the structural system, i.e. Tiris faults.

Gravity anomaly data is used in modelling the Lawu volcano fault. The fault modelling uses a total of 10,126 data points for free air anomaly GGMplus 2013 from http://ddfe.curtin.edu.au/ with a north-south direction with a grid of ± 200 meters. Separation of regional and residual anomalies using a moving average filter and Modelling using the forward modelling method. The modelling results show the distribution of rock densities of 2.52 gr/cm3 and 2.25 gr/cm3, which are composed of tuff and breccia with lava insertion, andesite lava with a density of 2.48 gr/cm3 and 2.9 gr/cm3, tuff lapilli, and pumice stone with a density of 2.35 g/cm3 and the last is andesite and basalt rocks with a density of 2.94 g/cm3. The modelling results also show two faults, namely the Sidoramping-Lawu normal fault and the Cemorosewu fault. From the type of rock and the location of the fault, it can be seen that Mount Lawu is an area highly vulnerable to landslides.

The completion of gravitational data inversion results in a smooth recovered model. GRAV3D is one software that can be used to solve 3D inversion problems of gravity data. Nevertheless there are still fundamental problems related to how to ensure the validity of GRAV3D to be used in 3D inversion. One approach used is to use lower bounds as inversion parameters. In this study lower bounds are set from to . The results obtained show that the use of lower bounds decreases resulting in a larger data misfit which means that the more data that meets the tolerance calculation, the better recovered model produced.

Yogyakarta earthquake, Mw 6.3, 27 May 2006 had killed 5,571 victims and destroyed more than 1 million buildings. This incident became the most destructive earthquake disaster over the last 11 years in Indonesia. Earthquake mitigation plan in the area has been carried out by understands the location of the fault. The location of the fault is still unclear among geoscientists until now. In this case, analysis of the aftershocks using oct-tree importance sampling method was applied to support the location of the fault that responsible for the 2006 Yogyakarta earthquake. Oct-tree importance sampling is a method that is recursively subdividing the solution domain into exactly eight children for estimating properties of a particular distribution. The final result of the subdividing process is a cell that has a maximum Probability Density Function (PDF) and identified as the location of the hypocenter. Input data consists of the arrival time of the P wave and S wave of the aftershocks catalog from 3-7 June 2006 and the coordinate of the 12 seismometers, and 1D velocity model of the study area. Based on the hypocenter distribution of the aftershocks data with the proposed method show a clearer trend of the fault compared with the aftershocks distribution calculated with theHypo71program. The fault trend has a strike orientation of N 42° E with a dip angle of 80° parallel with the fault scarp along the Opak River at the distance of about 15 km to the east. This fault trend is similar with the fault orientation obtained using the Double Difference Algorithm.

The existence of seismic wave velocity difference in the Earth crust and mantle creates the possibility to use earthquake data for estimating the crustal thickness utilizing the Ps conversion phase in the boundary. The radial component signal was deconvolved from the vertical component in the frequency domain to estimate receiver function for Indonesia region. We implemented the water level deconvolution techniques with a Gaussian filter of 2.5 Hz to eliminate the high frequency noise in the receiver function. The H-k stacking technique was performed to all receiver functions from each event to predict the crustal thickness and the Vp/Vs ratio below the stations. We analyzed ten azimuthally distributed teleseismic earthquakes recorded by 108 stations of BMKG. The result shows that the crustal thickness in Indonesia varies from 20 to 39.9 km. The western part of Sumatera, northern part of Sulawesi Island, and North Maluku region show generally thinner crust with value about 20 to 25 km. The North Sumatera, Central Java, and East Java show a considerably thicker crust of up to 36 km. Furthermore, our result also reveals a difference of crustal thickness about 5 km with the previous studies.

On May 27, 2006, 05:54 am local time, a moderate crustal earthquake of magnitude Mw 6,3 struck the Yogyakarta province, especially in the Bantul regency in the south part of the province. The earthquake damaged or destroyed more than 400,000 houses and buildings and caused more than 5,700 people killed. Several earthquake stations recorded the ground vibration caused by the mainshock very well, except at the stations closest to the earthquake source, namely YOGI in Gamping, West of Yogyakarta, which experienced saturation due to significant vibration. Therefore, information about the maximum ground acceleration near the source is yet not known. We model the ground vibrations near the earthquake source using a stochastic Green’s Function approach to obtain information about the ground motions’ maximum amplitude. The earthquake source parameters we referred to is the moment tensor solution from the Harvard Moment Tensor. The calculations show that the amplitude is consistent with observations recorded at the BJI Banjarnegara (0.04g) and YOGI Yogyakarta (0.3g).

The volcanic warning system in Indonesia is divided into four levels namely normal, waspada, siaga and awas. Based on the setting above, a study is needed to design a volcanic activity forecast system using temperature sensors, SO2, CO2 concentration, as well as vibration. The formulation of determining the conditions of volcanic activity is carried out by using fuzzy logic. Volcanic activity measurements are carried out in real time and continuously. Fuzzy logic has been used in the process of determining alert level of volcanic activity based on measured parameters. There are 53 fuzzy rules to determine volcano activity. Best predictions come from the combination of all sensors into a volcano monitoring and forecast system.

Indonesia has the highest number of active volcano all over the world. There were 63 eruptions with more than 70000 casualties from last year eruptions. To minimize the effect of this disaster, we have developed a volcano early warning system for Indonesian volcano. The main part of the system is volcano monitoring system. A system based on Internet of Things (IoT) has been developed to monitor some activities of a volcano. The physical parameters of these activities are indicated by the changing of temperature, gases (sulphur dioxide and carbon dioxide) concentration, vibration and landslides. The system consists of these parameter sensors, a microcontroller, a solar cell and a Long Range Radio (LoRa) for data transmission to the base station. The system has been tested in laboratory environment for the solar cell, sensors and radio communication. The solar cell could generate 18.81 Volt voltage and 0.23 Ampere current. The temperature sensor has been calibrated for until 51°C measurement (volcano normal condition), while the gas sensor could properly detect the gas until 8 ppm according to the calibration result. After Fast Fourier Transform (FFT) analysis the vibration sensor detected almost zero frequency with 0.168 m/s2, 0.0168 m/s2 and 1.125 m/s2 X, Y and Z axis zero offset respectively. In addition, the landslide had maximum about 4° degraded land slope error. Moreover, only 4% (maximum) percentage error rate (PER) shown by the radio for about 400 m data communication. Furthermore, the physical parameter data acquired then be real-time displayed using Node-red dashboard which can be accessed by the user or other parties who need the information.

Small island regions are facing disaster risks due to their exposure to various hazards, e.g. floods, landslide, and earthquake. In order to achieve long-term disaster resilience, one of the significant strategies is applying spatial planning based on disaster risk reduction. Methods for multi-hazard risk assessment and risk analysis have been broadly discussed, nevertheless, its implementation in spatial planning is inadequate. In this study, we conducted a multi-hazard risk mapping of Sangihe Island and reviewed its spatial plan. It is identified that disaster risk analysis hardly meets its standard in consequence of insufficient secondary data availability. Also, the spatial plan merely utilizes hazard maps for consideration, not yet as risk analysis, resulting in allocating vital elements in high-risk areas. Hence, secondary data support is necessary for accordance with the needs of standardized risk analysis and is updated regularly. Furthermore, integration of risk analysis into spatial planning is required to determine the direction of development, which not only reduces exposure to hazards but emphasizes more towards the capacity building to reduce vulnerability.

The seismic data acquisition system from analog to digital data converter has been integrated to develop acquisition device. Contrary to the digitizers currently in use, seismic data acquisition using PC/104, or industrial personal computer, turned out to be able to produce a less expensive digitizer (analog to digital converter) proven able to overcome issues of portability, efficiency, and durability. PC/104 used in this study was Arbor production with the EmCORE n-511 serial number within operating system, and the programming languages are DOS 6.02 and C, respectively. This research resulted in a design of a prototyping device based on PC/104 and created a program to record seismic data. The program was compiled in the Microsoft Windows XP operating system environment using Borland C 5.02 software. The input range of the data acquisition system that has been tested is ± 10 V. The performance test results show a resolution of ± 0.915 mV, a linearity of 0.2% full-scale reading, instrument work noise is ± 1.2 mV with a maximum frequency distortion of 2%. The instrument performs well at a rate of 10 Hz to 5000 Hz, but the software has a limited capacity of only 1000 Hz. From the results of a comparative test with Digitizer Guralp Type CGM-DM16R8, the value of the RMS error is 4.64%.

Analisis dan modeling mengenai struktur geologi Pulau Sulawesi khususnya wilayah Sulawesi Tengah sangat menarik sebab memiliki kompleksitas yang tinggi sebagai akibat interaksi dinamis dari tiga lempeng utama dunia. Ketiga lempeng tersebut yakni lempeng India Australia, lempeng Pasifik dan lempeng Eurasia yang dalam pergerakannya saling bertemu yang mengakibatkan daerah ini mengalami deformasi kerak bumi yang aktif. Salah satu bentuk deformasi dari gerakan dinamik adalah terbentuknya sesar Palu Koro. Metoda yang digunakan untuk mengkaji sesar tersebut digunakan metoda gayaberat. Hasil yang diperoleh menunjukkan bahwa sesar Palu Koro merupakan sesar geser mengiri dan normal. Model patahan bawah permukaan sesuai dengan penampakan morfologi topografi daerah penelitian. Bagian struktur bawah permukaan telah mengalami deformasi yang kuat dimana semua model strukturnya berbentuk struktur sekunder tidak ditemukan lagi struktur primer. Didapatkan pula batuan intrusi berkisar dari dua sampai tiga intrusi yang terlihat pada sayatan AA’. Formasi batuannya berjumlah enam jenis, yaitu batuan aluvium, formasi pakuli, formasi latimojong, kompleks wana, kompleks gumbasa dan batuan intrusi.

The objectives of this research are to model the earth crust and Mohorovicic depth at part of Central java island. The subsurface modeling has been carried out using the inversion of receiver function techniques and stacking H-κ. The methodology of this research using the inversion technique and the H-κ stacking technique to obtain subsurface structures and determine the depth of Mohorovicic discontinuity. The results of this research are the average depth of Mohorovicic discontinuity is 33.54 km and the value of κ 1.65. The depth of Mohorovicic’s discontinuity in Yogyakarta and Semarang is 25-33km. Based on the inversion technique, there is a low speed anomaly between Mt. Merapi and Mt. Lawu at a depth of 11-19 km known as MLA (Merapi Lawu Anomaly) under the Kendeng Zone. The P wave velocity at a depth of 11 Km has a pattern which is interpreted as the long subduction zone of the dominant Maratus trend. The fact that proves the old subduction is the P wave velocity pattern near Karangsambung which has melange outcrops.

In this study, we used receiver function technique to determine the shear wave velocity profile of the crust and uppermost mantle beneath the eastern part of Indonesia region. We use six BMKG’s permanent stations in the Eastern Indonesia region that recorded about 70 teleseismic events. The receiver function inversion shows a significant variation of sediment thickness layer from about 2 to 4 km in the West Papua region. The crustal thickness variation is estimated at 17 km to 19 beneath Ternate Island and northern Sulawesi, whereas the crustal thickness beneath of the West Papua Region is at 24 km and 37 km. The lithosphere thickness estimate at 40 km to 48 km in Ternate Island and northern Sulawesi while the West Papua Region is around 60 km to 76 km. We found the evidence for a strikingly low-velocity layer starting at about 28 to 30 km depth beneath Ternate islands and northern Sulawesi that may relate to the partial melting zone beneath the active volcano in those areas.

One-dimensional modeling of magnetotelluric (MT) data has been performed using an online application on a web-based virtual private server. The application was developed with the Python language using the Django framework with HTML and CSS components. The input data, including the apparent resistivity and phase as a function of period or frequency with standard deviation, can be entered through an interactive web page that can be freely accessed at https://komputasi.geofisika.ugm.ac.id. The subsurface models, represented by resistivity as a function of depth, are iteratively improved by changing the model parameters, such as the resistivity and the layer depth, based on the observed apparent resistivity and phase data. The output of the application displayed on the screen presents resistivity as a function of depth and includes the RMS error for each iteration. Synthetic and real data were used in comparative tests of the application's performance, and it is shown that the application developed accurate subsurface resistivity models. Hence, this application can be used for practical one-dimensional modeling of MT data. One-dimensional inversion MT data is performed using an online application.Input data can be entered or imported through an interactive web page.The application's performance showed accurate subsurface resistivity models.