Penerapan Fungsi Green dari Persamaan Poisson pada Elektrostatika

The Dirac delta function is a function that mathematically does not meet the criteria as a function, this is because the function has an infinite value at a point. However, in physics the Dirac Delta function is an important construction, one of which is in constructing the Green function. This research constructs the Green function by utilizing the Dirac Delta function and Green identity. Furthermore, the construction is directed at the Green function of the Poisson's equation which is equipped with the Dirichlet boundary condition. After the form of the Green function solution from the Poisson's equation is obtained, the Green function is determined by means of the expansion of the eigen functions in the Poisson's equation. These results are used to analyze the application of the Poisson equation in electrostatic.

The Effectiveness of Clarke Wright and Sequential Insertion Algorithm in Distribution Routing Aqua

With the Multiple Trips condition, the results obtained for the optimal distance route that starts and stops at PT. Tirta Investama Medan with Clarke Wright Algorithm at t = 1 is 22 km and at t = t + 1 is 15.2 km. While the optimal travel distance route with the Sequential Insertion Algorithm at t = 1 is 15.05 km, and at t = t + 1 is 22.9 km. Clarke Wright Algorithm looks for an optimal solution to get the best route, while Sequential Insertion Algorithm has an excess in the election of a customer by considering customer position with available insertion track location until all customer have been assigned. The Clarke Wright Algorithm obtained a total distance of 37.2 km. In comparison, the Sequential Insertion Algorithm solution obtained a total distance of 37.95 km. It can be concluded that the route formed using the Clarke Wright Algorithm in this case is more effective than using the Sequential Insertion Algorithm.

Aplikasi Pemetaan terkait Semi-Inner Produk pada Ruang Bernorma Real

In this article, we give the properties of mappings associated with the upper semi-inner product , lower semi-inner product and Lumer semi-inner product which generate the norm on a real normed space. Furthermore, we establish applications to the Birkhoff orthogonality and characterization of best approximants.

Students’ Metacognitive Process in Mathematical Problem Solving Based on Cognitive Style

This study is a qualitative literature review aimed to describe junior high school students’ metacognitive process in mathematical problem solving based on field independent and field dependent cognitive style. The research was done based on these following steps: 1) Data library relevant to variable and in accordance to the data source criteria was collected; 2) the data library was classified according to the grade and the subjects; 3) the data was analyzed. The instruments used in this study were the researchers and interview. The interview was conducted to confirm the classified data. Based e this study, it can be concluded that students using field independent style, competently can employ metacognitive process in planning, monitoring, and evaluating because they can write down the known fact and the question using mathematical symbol, choose the appropriate strategy, and answer the question thoroughly. Students using field dependent style were having difficulties in writing down the known fact and the question using mathematical symbol, choosing an appropriate strategy, and answering the question thoroughly.

Estimasi Parameter Model Autoregressive dengan Metode Yule Walker, Least Square, dan Maximum Likelihood (Studi Kasus Data ROA BPRS di Indonesia)

The Autoregressive model is a time series univariate model for stationary models. In estimating parameters on this model can be done by several methods, namely yule-walker method, Least Square, and Maximum Likelihood. Each method has a different principle for estimating model parameters so that the results obtained will also be different. Based on this, in this study, the AR(1) model parameter estimation was estimated by generating data simulated 1000 times to see the performance of Yule-Walker, Least Square, and Maximum Likelihood methods. In addition, the comparison of these three methods is also done on ROA BPRS data that follows the AR(1) model. The results showed that the Maximum Likelihood method was able to provide mode results and comparison of the most suitable estimation results for simulation data and produce the smallest MAE values in the data in sample and MAPE, MSE, and MAE the smallest in the out sample data. These results show that the Maximum Likelihood method is the best method for modeling data that follows the AR(1) model.

A Weighted Markov Chain Application to Predict Consumer Price Index When Facing Pandemic Covid-19

Covid-19 is an infectious disease caused by acute respiratory syndrome coronavirus 2 (severe acute respiratory syndrome coronavirus 2 or SARS-CoV-2). It makes the decrease of people's purchasing power. Meanwhile, the economic growth indicates the success of a country's economic development. Therefore, the Consumer Price Index occurs Inflation and Deflation, which is commonly referred to in the economy as the Consumer Price Index. This study aimed to apply a weighted Markov chain method to predict the consumer price index in the future. The satisfactory results obtained by researchers in predicting the consumer price index are in, the chance is 84.34% and the 12th month has a 78.54% chance.

Students Team Achievement Division (STAD): Model Pembelajaran Kooperatif untuk Meningkatkan Kerja Sama Peserta Didik

The research aimed to increase students' cooperation skills and to describe mathematics learning quality through cooperative learning models, types Students Team Achievement Division (STAD). This research is a classroom action research using model of Kemmis Taggart. The subject is 11 grades students of Mathematics and Natural Science 3 in 1 Wates Senior High School. The findings indicated that the learning model, style Students Team Achievement Division (STAD), could improve students' cooperation skill. The excellent implementation is shown by an improvement in the percentage of student cooperation in mathematics instruction, namely from the results of the first cycle, the average performance of cooperation is 67.8% of students in the high and very high category and an increase in the second cycle by 82.2% of students in the high and very high category. The results of observations of the implementation of mathematics learning using cooperative learning model, type Students Team Achievement Division (STAD), in cycle I revealed a percentage of 91%, which increased to 96% in cycle II.

Pengategorian Provinsi Berdasarkan Kelompok Sukses dan Gagal dalam Penanganan Pandemik Covid-19 di Indonesia Menurut Analisis Diskriminan

An assessment of categorizing the handling of Covid-19 by the Regional Government is needed, this categorization includes the handling performance (KP) and the death rate (TK) of Covid-19. This was done to see how serious the local government is in handling Covid-19. The approach in this study uses a descriptive approach, this approach aims to describe or describe the categorization of provinces based on groups that have succeeded and failed in handling the Covid-19 pandemic in Indonesia. In this research, the method used is quantitative method. The quantitative approach used is discriminant analysis. The conclusion of this study is that the discriminant function formed in this study is Z = 0.893 KP + 0.451 TK. The results of eigenvalues in this study indicate that the magnitude of Canonical Correlation is 0.797 or the amount of Square Canonical Correlation (CR2) = (0.797) 2 or equal to 0.635. So it can be concluded that 63.5% of the variation between groups of successful and failed provinces can be explained by the discriminant variables of the KP and TK ratios. The view of the matrix structure in this study shows that the amount of loading for KP is 0.842 and the amount of loading for TK is 0.332. The two variables of the Covid 19 handling ratio are high enough so that the discriminant score can be interpreted as a measure of the success of the handling of Covid 19 at the Provincial Government. Meanwhile, the results of the classification matrix show that 32 observations have been classified correctly and only two observations are classified incorrectly, namely the observations number 18 and 19, so the classification accuracy is (32/34) or 94.1%.