Penerapan Metode Double Exponential Smoothing dan Moving Average pada Peramalan Permintaan Produk Gasket Cap di PT. Nesinak Industries

PT. Nesinak Industries is a company which focuses on the manufacturing process of an electronic component as well as automotive components (vehicle). In business activities, such as production, a strategy is required to survive in competition. Planning and forecasting are a strategy that can be implemented to accomplish these goals. In this study, the data used are previous sealing application data from January 2019 to March 2021. The objective of this study is to forecast product demand over the next period in order to be able to respond to customer demand. Data processing in this study utilize the Brown exponential double smoothing method and the moving average is then determined with the lowest MAPE (Mean Absolute Percentage Error) value to be used for the company’s product demand prediction calculations. The value of taken from Brown's exponential dual smoothing method is the value of with the two lowest error values from 0.1 to 0.9, whose value with the least error value is = 0.8 and = 0.9. In terms of the moving average method, the researchers tested a period of three months and a period of four months. In the MAPE calculation, the results of exponential double smoothing = 0.8 of 26.92 %, exponential double smoothing = 0.9 of 26.22 %, moving average n = 3 of 32.46%, and moving average n = 4 of 34.77%.

Application Of The Hybrid Method Nonlinear Regression With Modified Logistic Growth Model - Exponential Double Smoothing For Forecasting Covid-19 Cases In Indonesia And Armenia

Since the first cases of Covid-19 (Corona Virus Disease-19) infection were officially recognized and recorded in Indonesia on March 2, 2020 and March 1, 2020 in Armenia, the addition of new cases has not shown any indication of sloping. The relatively high number of new cases indicates that Indonesia has not yet passed the peak of the pandemic. As for Armenia, the addition of new cases indicates a new pandemic peak to be faced. In these conditions, an important question for decision makers (the Government) to find answers to is when and at what level of total cases will the COVID-19 pandemic end in Indonesia or the second wave in Armenia. Based on this, the forecasting method of Hybrid Nonlinear Regression With Modified Logistic Growth Model - Double Smoothing Exponential and Classical methods is used to predict the Covid-19 cases that occur in Indonesia and Armenia. Based on the model formed, the peak of Covid-19 cases in Indonesia is predicted to occur on November 26, 2020, with the number of cases reaching 5968 cases. As for Armenia, the peak of Covid-19 cases will occur on November 15, 2020, with the number of cases reaching 3098 cases. Covid-19 in both countries is predicted to decline and be constant in 2021. For the country, Indonesia is predicted to begin to stabilize and be controlled in July - August 2021. As for Armenia, Covid-19 is predicted to be under control and approaching 0 cases in February - March 2021.

Application Of The Hybrid Method Nonlinear Regression With Modified Logistic Growth Model-Exponential Double Smoothing For Forecasting Covid-19 Cases In Indonesia And Armenia

Since the first cases of Covid-19 infection were officially recognized and recorded in Indonesia on March 2, 2020 and March 1, 2020 in Armenia, the addition of new cases has not shown any indication of sloping. The relatively high number of new cases indicates that Indonesia has not yet passed the peak of the pandemic. As for Armenia, the addition of new cases indicates a new pandemic peak to be faced. In these conditions, an important question for decision makers (the Government) to find answers to is when and at what level of total cases will the COVID-19 pandemic end in Indonesia or the second wave in Armenia. Forecasting method of Hybrid Nonlinear Regression With Modified Logistic Growth Model - Double Smoothing Exponential and Classical methods is used to predict the Covid-19 cases that occur in Indonesia and Armenia. Based on the model formed, the peak of Covid-19 cases in Indonesia is predicted to occur on November 26, 2020, with the number of cases reaching 5968 cases. As for Armenia, the peak of Covid-19 cases will occur on November 15, 2020, with the number of cases reaching 3098 cases. Covid-19 in both countries is predicted to decline and be constant in 2021. For the country, Indonesia is predicted to begin to stabilize and be controlled in July - August 2021. As for Armenia, Covid-19 is predicted to be under control and approaching 0 cases in February - March 2021. Forecasting models for the Covid-19 cases in Indonesia and Armenia are different, where for the Covid-19 case in Indonesia the Nonlinear Regression with Logistic Growth Model can be used and for the country of Armenia, the Nonlinear Regression with Modified Logistic Growth Model must be used because it has 2 peak cases. Hybrid method is a very good method for optimizing forecast results. Its application in the Covid-19 case in Indonesia and in Armenia shows that the Hybrid method produces a better MAPE value than the Nonlinear Regression with Logistic Growth Model alone or the Exponential Double Smoothing method alone

Nonparametric Range-Based Double Smoothing Spot Volatility Estimation for Diffusion Models

We consider nonparametric spot volatility estimation for diffusion models with discrete high frequency observations. Our estimator is carried out in two steps. First, using the local average of the range-based variance, we propose a crude estimator of the spot volatility. Second, we use usual nonparametric kernel smoothing to reconstruct the volatility function from the crude estimator. By inference, we find such a double smoothing operation can effectively reduce the estimation error.

Topology Optimization for FDM Parts Considering the Hybrid Deposition Path Pattern

Based on a solid orthotropic material with penalization (SOMP) and a double smoothing and projection (DSP) approach, this work proposes a methodology to find an optimal structure design which takes the hybrid deposition path (HDP) pattern and the anisotropic material properties into consideration. The optimized structure consists of a boundary layer and a substrate. The substrate domain is assumed to be filled with unidirectional zig-zag deposition paths and customized infill patterns, while the boundary is made by the contour offset deposition paths. This HDP is the most commonly employed path pattern for the fused deposition modeling (FDM) process. A critical derivative of the sensitivity analysis is presented in this paper, which ensures the optimality of the final design solutions. The effectiveness of the proposed method is validated through several 2D numerical examples.

An Image-Based Double-Smoothing Cohesive Finite Element Framework for Particle-Reinforced Materials

In order to simulate the fracture process of particle-reinforced materials on the micro-scale, an image-based double-smoothing cohesive finite element framework is proposed in the present paper. Two separate smoothing processes are performed to reduce the noise in the digital image and eliminate the jagged elements in the finite element mesh. The main contribution of the present study is the proposed novel image-based cohesive finite element framework, and this method improved the quality of the meshes effectively. Meanwhile, the artificial resistance due to the jagged element is reduced with the double-smoothing cohesive finite element framework during the crack propagation. Therefore, the image-based double-smoothing cohesive finite element framework is significant for the simulation of fracture mechanics.

TENDENCJE KONSUMPCJI WYROBÓW ALKOHOLOWYCH W EUROPIE W LATACH 2016-2019

The paper presents the results of research on the determination of the trend of consumption of pure alcohol per one person in the years 2017 - 2019 and an analysis of the appropriateness of applying the division of Europe into regions according to the UN M49 classification. The study was conducted for European countries, divided into Northern Europe, Southern Europe, Western Europe and Eastern Europe. Holt's exponential double smoothing method was used in the forecasting process. As a result of the conducted research, general downward trends of the phenomenon in the discussed period were demonstrated, as well as the possibility of using territorial division according to the average volume of total alcohol consumption in individual European countries.

Residential load event detection in NILM using robust cepstrum smoothing based method

Event detection has an important role in detecting the switching of the state of the appliance in the residential environment. This paper proposed a robust smoothing method for cepstrum estimation using double smoothing i.e. the cepstrum smoothing and local linear regression method. The main problem is to reduce the variance of the home appliance peak signal. In the first step, the cepstrum smoothing method removed the unnecessary quefrency by applying a rectangular window to the cepstrum of the current signal. In the next step, the local regression smoothing weighted data points to be smoothed using robust least squares regression. The result of this research shows the variance of the peak signal is decreased and has a good performance with better accuracy. In noise enviromment, performance prediction quite good with values greater than 0.6 and relatively stable at values above 0.9 on SNR> 25 for single appliances. Furthermore, in multiple appliances, performance prediction quite good at SNR> 20 and begins to decrease in SNR <20 and SNR> 25.