Sinabung is a small stratovolcano located in northern Sumatra about 50 km northwest of the Toba caldera. On August 27, 2010, it was confirmed that Sinabung experienced a phreatic eruption for the first time in history. Initially the eruption formed a lava dome that fell out on January 10, 2014 forming pyroclastic density currents. An increase in pore fluid pressure in the crust supports Coulomb Failure Friction. Positive coulomb stress values are thought to trigger Sinabung activity. The research uses a combination of Monte Carlo simulation to predict the next earthquake parameters and coulomb stress analysis to determine the direction and value of stress . The Monte Carlo simulation produces earthquake parameter prediction, longitude 98o latitude 3.175o depth 104.5 meters, Mw 6.0, strike 28.125 o, slip 42o, dip 44.17o. Coulomb Stress analysis of the combined 2001-2021 earthquake data produces an average coulomb value of 0.24 bar, 0.14 bar shear, 0.25 bar normal and the direction of the stress vector to the southwest of Mount Sinabung. The results of the combined coulomb stress analysis and Monte Carlo simulation predict the direction of pyroclastic flows to the northeast, east, and southeast of Mount Sinabung, in accordance with the direction that is inversely proportional to positive stress so that the area needs to receive early warning of volcanic eruption natural disasters in 2022.
Network analysis is part of a project that requires time for each network activity. To produce a particular project there is more than one job/event that must be done. Each job/event is interconnected and placed in order according to the management of its implementation. In network projects, it is necessary to plan and supervise systematically, in order to obtain work efficiency. The network is represented in symbols and arrows. In this study, the problem-solving network analysis was solved using the CPM (Critical Path Method) method and with a linear programming model using the help of excel-solver and Lingo. This study aims to compare the two methods in solving network analysis problems. Based on the analysis, it is found that by using the CPM method, more critical paths are obtained than the linear programming method. With the increasing number of critical paths obtained, it is hoped that the management can determine project priorities to maintain the project schedule to be completed on time.
Estimasi parameter adalah praktik umum dalam statistik. Maximum Likelihood adalah metode estimasi parameter berdasarkan pendekatan distribusi dengan cara memaksimalkan fungsi likelihood. Mean, deviasi standar, proporsi dan lain-lain merupakan perkiraan nilai parameter dengan menggunakan data atau sampel yang dapat diambil dari populasi tersebut. Algoritma Newton Raphson adalah prosedur iteratif yang digunakan untuk menyelesaikan persamaan non-linier. Fokus makalah ini adalah mengestimasi parameter data yang berdistribusi normal menggunakan Maximum Likelihood berdasarkan algoritma iterasi Newton Raphson dengan program matlab.
In statistics, parameter estimation is the estimation of a population using sample data. A population data certainly has a certain distribution. Fisher Scoring is a form of Newton's method which is commonly used in solving the maximum likelihood equation. The focus of this research is to estimate distributed data using the fisher scoring algorithm
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