Things to Remember About Exponential Smoothing in Excel The alpha value will be 1 - Dumping value and vice versa. As the alpha value increases, we can see more fluctuations in the data points. Labels need to be ticked if the input range includes headings. Ideal dumping values should be 0.2 to 0.3 Example: Exponential Smoothing in Excel Step 1: Click on the Data Analysis button. Go to the Data tab along the top ribbon and click the Data Analysis... Step 2: Choose the Exponential Smoothing option and click OK. Step 3: Fill in the necessary values Double Exponential Smoothing (with Implementation in Excel) The double exponential smoothing algorithm uses the same idea as simple exponential smoothing. It uses historical values for making the predictions and assigning the weights in an exponentially increasing manner (higher weight to the recent observations). Additionally, the double exponential smoothing also considers the 'trend' of the series Exponential Smoothing in Excel. Exponential Smoothing in Excel is an inbuilt smoothing method used for Forecasting, Smoothing the data, trend projection. To access, Exponential Smoothing in Excel, go to the Data menu tab and, from the Data Analysis option, choose Exponential Smoothing

Do It Yourself — Simple Exponential Smoothing with Excel. In this article, you will implement, in excel, a simple exponential smoothing forecast model. 1. We start our data table by creating three columns: Date on column A; Demand on column B; Forecast on column C; 2. Next to t his, let's add a cell with alpha (F1 in our example). Don't forget to clearly indicate that this cell is alpha Excel Data Analysis Tool: Excel provides the Exponential Smoothing data analysis tool to simplify the calculations described above. To use this tool for Example 1, select Data > Analysis|Data Analysis and choose Exponential Smoothing from the menu that appears Exponential smoothing forecasting in Excel is based on the AAA version (additive error, additive trend and additive seasonality) of the Exponential Triple Smoothing (ETS) algorithm, which smoothes out minor deviations in past data trends by detecting seasonality patterns and confidence intervals * This video shows1) How to calculate exponential smoothing forecasts in Excel2) How to calculate MAD, MSE, and MAPE in Excel*.3) How to use Excel Solver to fin.. Die exponentielle Glättung (englisch exponential smoothing) ist ein Verfahren der Zeitreihenanalyse zur kurzfristigen Prognose aus einer Stichprobe mit periodischen Vergangenheitsdaten. Diese erhalten durch das exponentielle Glätten mit zunehmender Aktualität eine höhere Gewichtung

Exponential Smoothing in Excel About Press Copyright Contact us Creators Advertise Developers Terms Privacy Policy & Safety How YouTube works Test new features © 2021 Google LL The data in Figure 3 of Simple Exponential Smoothing (as well as previous figures on that webpage) shows a distinct upward trend. The Moving Average and Simple Exponential Smoothing methods don't adequately model this, but Holt's Linear Trend Method (aka Double Exponential Smoothing) does.This is accomplished by adding a second single exponential smoothing model to capture the trend. In the Holt-Winters Method (aka Triple Exponential Smoothing), we add a seasonal component to Holt's Linear Trend Model. We explore two such models: the multiplicative seasonality model and the additive seasonality model. We consider the first of these models on this webpage. See Holt-Winters Additive Model for the second model. Let c be the length of a seasonal cycle. Thus c = 12 for months.

In this tutorial we will learn how to implement Exponential smoothing in Excel for a time series data. What is Exponential smoothing? Statistical smoothing technique for detecting significant changes in data by ignoring the fluctuations irrelevant to the purpose Exponential Smoothing forecasts demand in the next ti... Learn how to use exponential smoothing to forecast future needs in Excel 2013 for Time Series Analysis **Exponential** **Smoothing** Forecast **Excel** 2016 Data Analysis Toolpak - YouTube. **Exponential** **Smoothing** Forecast **Excel** 2016 Data Analysis Toolpak. Watch later * Exponential Smoothing in Excel Exponential Smoothing is used to forecast the business volume for taking appropriate decisions*. This is a way of Smoothing out the data by eliminating much of random effects. The idea behind Exponential Smoothing is just to get a more realistic picture of the business by using the Microsoft Excel 2010 and 2013

Exponential smoothing is a rule of thumb technique for smoothing time series data using the exponential window function.Whereas in the simple moving average the past observations are weighted equally, exponential functions are used to assign exponentially decreasing weights over time. It is an easily learned and easily applied procedure for making some determination based on prior assumptions. 用Excel實作指數平滑法 / Exponential Smoothing in Excel10/23/2016 研究方法 , Software/Office , Statistics 0 CommentsEdit Copy Download. 指數平滑法 是時間序列分析中用來預測的一種常用的做法。. 該做法是改良自移動平均法，將越久遠的觀察值對預測的影響降低。. 指數平滑法可以直接用Excel的「資料分析」工具來計算，我就根據「 数据建模与决策 」中「第11章 时间序列分析和预测」的. Several methods available in Excel using the XLSTAT statistical software. Several smoothing methods are available in the XLSTAT-Forecast solution. They are described below. Simple exponential smoothing. This model is sometimes referred to as Brown's Simple Exponential Smoothing, or the exponentially weighted moving average model. Exponential smoothing is useful when one needs to model a value. The General Exponential Smoothing Function not only supports prior smoothing models covered by the Simple, double and triple exponential smoothing functions, but it implements additional types for trend and seasonal components. Furthermore, the General Exponential Smoothing Function supports data prior-transformation and Chatfield correction/adjustment for 1 st order autocorrelation in the. In this tutorial we'll demonstrate the double exponential smoothing in NumXL. For the sample data we are using weekly demand volume for a hypothetical product. Holt's double exponential smoothing is best used with data that exhibits stable trend over time and no seasonality, so let's examine the data set for the trend assumption. Using Excel's built-in chart function draw a trend through the data

- Forecasting in Excel using exponential smoothing can be done easily using the 'Forecast' tool. Under the hood, it uses the 'FORECAST.ETS' function. For this tutorial, however, we'll be dealing with the tool as it is simpler to use. Since we're forecasting, it's important that our data are summarized in consistent time periods. As.
- How to perform exponential smoothing in Excel 2013 - YouTube. How to perform exponential smoothing in Excel 2013. Watch later. Share. Copy link. Info. Shopping. Tap to unmute. If playback doesn't.
- Exponential smoothing is a way of analyzing data from specific periods of time by giving more importance to the newer data, and less importance to the older data. This method produces smoothed data, or data that has the noise removed, allowing patterns and trends to be more visible

From time to time people have asked me how to implement Holt Winters (trend-seasonal exponential smoothing) in Excel. Let me start by saying that although Excel is probably the most common forecasting tool in business, it is also not a good one. It does not provide many useful options and tools and there is plenty of space for mistakes. I have produced a small example of Holt Winters that you. #3 - Exponential moving average in Excel. It is similar to a simple moving average that measures trends over a period of time. While simple moving average calculates an average of given data, exponential moving average attaches more weight to the current data. Exponential moving average =(K x (C - P)) + P. Where, K = exponential smoothing. Exponential smoothing is a time series forecasting method for univariate data that can be extended to support data with a systematic trend or seasonal component. It is a powerful forecasting method that may be used as an alternative to the popular Box-Jenkins ARIMA family of methods. In this tutorial, you will discover the exponential smoothing method for univariate time series forecasting

**Exponential** **Smoothing** in **Excel** is an inbuilt **smoothing** method used for Forecasting, **Smoothing** the data, trend projection. To access, **Exponential** **Smoothing** in **Excel**, go to the Data menu tab and, from the Data Analysis option, choose **Exponential** **Smoothing**. Select the input range which we want to smooth and then choose the dumping factor, which should be between 0 and 1 (1 - α) and then select. Double Exponential Smoothing (with implementation in Excel) Triple Exponential Smoothing (with implementation in Excel) Introduction to Time Series Forecasting. We deal with time series data almost daily (without realizing it half the time). In our day to day lives, we often make conclusions about certain things based on our past observations and experiences. For instance, if the stock price. What is Exponential smoothing? Statistical smoothing technique for detecting significant changes in data by ignoring the fluctuations irrelevant to the purpose. Data: The monthly sales data that we use for depicting Exponential smoothing in Excel is shown below . Step 1: First, let's plot our time series, which is shown below Do It Yourself — Simple Exponential Smoothing with Excel. In this article, you will implement, in excel, a simple exponential smoothing forecast model. 1. We start our data table by creating three columns: Date on column A; Demand on column B; Forecast on column C; 2. Next to t his, let's add a cell with alpha (F1 in our example). Don't forget to clearly indicate that this cell is alpha. Excel hat uns jedoch ein integriertes Tool zur Verwendung dieser Technik zur Verfügung gestellt, nachdem wir die Daten ausgewählt haben, die wir auf der Registerkarte Daten und dann in eingeben müssen Datenanalyse, bei der wir eine exponentielle Glättungstechnik finden. Was ist exponentielle Glättung in Excel? Exponential Smoothing ist eine der drei wichtigsten Methoden zur Umsatzprognose.

Excel Data Analysis Tool: Excel provides the Exponential Smoothing data analysis tool to simplify the calculations described above. To use this tool for Example 1, select Data > Analysis|Data Analysis and choose Exponential Smoothing from the menu that appears. A dialog box now appears which is similar to that shown in Figure 2 of Simple Moving Average, except that a Damping Factor field is. Exponential smoothing forecasting in Excel is based on the AAA version (additive error, additive trend and additive seasonality) of the Exponential Triple Smoothing (ETS) algorithm, which smoothes out minor deviations in past data trends by detecting seasonality patterns and confidence intervals. This forecasting method is best suited for non-linear data models with seasonal or other recurring. Exponential Smoothing is used to forecast the business volume for taking appropriate decisions. This is a way of Smoothing out the data by eliminating much of random effects. The idea behind Exponential Smoothing is just to get a more realistic picture of the business by using the Microsoft Excel 2010 and 2013 Exponential Smoothing in Excel https://www.buymeacoffee.com/DrDavidJohnkExponential Smoothing Forecasting Using Excel. Use MSE (Mean Squared Error), MAE (Mean Absolute Error), and MAPE (M..

In this video, we'll demonstrate the Holt-Winters' double exponential smoothing function in NumXL. Part 2: http://www.youtube.com/watch?v=0oeFyOZ7r_UFor more.. The FORECAST.ETS function in Excel is used to forecast data using an exponential smoothing algorithm. Exponential smoothing is a method in statistics used for smoothing time series data by assigning exponentially decreasing weights to future values over time. This differs from a simple moving average where past observations are weighted equally. The predicted value is a continuation of the. This video explains the concept of exponential smoothing forecast and demonstrates an example using excel.#exponentialSmoothing #forecasting #researchHUB.Vid.. Brown's Simple Exponential Smoothing in Excel (SESMTH) Jacquie Nesbitt January 17, 2013 03:53. Follow. Check out our Simple Exponential Smoothing tutorial below. The playlist contains tutorials that teach you how to utilize the optimization switch, calibrate with a training set, and calculate an in-sample forecast using NumXL. Optimization on Calibration Dataset Optimization Off Forecasting. Making a time-series forecast using exponential smoothing - Excel 201

The Exponential Smoothing tool in Excel calculates the moving average. However, exponential smoothing weights the values included in the moving average calculations so that more recent values have a bigger effect on the average calculation and old values have a lesser effect. This weighting is accomplished through a smoothing constant. To illustrate how the Exponential [ COVID-19 Information: The latest about how Temple is safeguarding our community. Read Mor Prognosefunktionen können verwendet werden, um zukünftige Werte basierend auf historischen Daten vorherzusagen. Diese Funktionen verwenden erweiterte Algorithmen für maschinelles Lernen, z. B. Exponential Triple Smoothing (ETS)

Select «Exponential Smoothing» from the proposed list of tools for statistical analysis. This alignment method is suitable for our dynamic series, the values of which fluctuate strongly. We fill the dialog box. The input interval is the range of sales values. The damping factor is the coefficient of exponential smoothing (default is 0.3). Output interval -is a reference to the upper left. These Excel templates for trend-adjusted smoothing work on all versions of Excel since 2007. Examples of a ready-to-use spreadsheet: Download this table in Excel (.xls) format, and complete it with your specific information. To be able to use these models correctly, you must first activate the macros at startup. To activate the smoothing methods dialog, launch XLSTAT, then select the XLSTAT.

You can implement such effective forecasting methods using Excel tools like exponential smoothing, regression construction, moving average. Let's consider the use of the moving average method in more detail. Use of moving average in Excel. The moving average method is one of the empirical methods for smoothing and forecasting time-series. The essence: the absolute values of a time-series. Forecast automatically with Excel in less than 5 minutes. Forecasting models and trendlines. Seasonality & triple exponential smoothing (easy ) Forecast examples of Covid Cases in the World, India and USA. Forecast examples of Sales Cars in the USA Excel 2011 for Mac Posts 157. Exponential Smoothing - Can you optimize the damping factor? Hi, I was looking at doing some exponential smoothing on sports data (I do least squares regression to try and predict future outcomes). I didn't realise that there was an add-in to do this for me and was trying to multiply the previous weeks results by say 0.95 as a factor (so they only counted 95% as.

Double Exponential Smoothing (Holt's method) This method involves computing level and trend components. Forecast is the sum of these two components. As shown in the below picture, equation for level component is similar to the previously discussed single exponential smoothing. As in the previous case, α is smoothing constant lies between 0 and 1 * 1*.1 简单指数平滑 simple exponential smoothing (SES) 对应的sm又是什么样的？今天我们就结合Excel 和 Evie... Holt Winter 指数平滑模型 BigData_Mining的博客. 07-19 5961* 1* 指数平滑法 移动平均模型在解决时间序列问题上简单有效，但它们的计算比较难，因为不能通过之前的计算结果推算出加权移动平均值。此外. 3.1 Using MS-Excel 2007..... 5 3.2 Using MS-Excel 2010..... 5 3.3 VBA requirements to run the ESM..... 5 4. How to use the Exponential Smoothing Macro.. 6 4.1 Introduction to the Graphical User Interface (GUI).. 6 4.2 Time series data.. 7 4.3 Generating the forecasts.. 8 5. Using the damped trend exponential smoothing method with a logarithmic transformation: A demonstration. **Exponential** **Smoothing** in **Excel** 2016 & 2013. Watch the video or read the steps below: **Exponential** **Smoothing** in **Excel** 2016 & 2013: Overview. **Exponential** **smoothing** is a way to smooth out data for presentations or to make forecasts. It's usually used for finance and economics. If you have a time series with a clear pattern, you could use moving averages — but if you don't have a clear. The way exponential smoothing works, the weight given to the very first few values is very, very small, and thus the impact of the seed is almost negligible. Okay, you know the drill. Next comes the Excel screen flow videos. After these, you've got quizzes to practice and discussion boards to have a Q&A session with your peers in the course. You've also got an assessment do this week to see.

- ating outliers from datasets to make the patterns more noticeable. The random method, simple moving average, random walk, simple exponential, and exponential moving average are some of the methods used for data smoothing
- Exponential Smoothing uses a weighted average of past time series values as a forecast for future data points. Where. α decides how much smoothing the model is doing. Alternatively, Simple exponential smoothing can also be expressed by: The new forecast is equal to the previous forecast, plus an adjustment, which is the smoothing constant α.
- Exponential Smoothing - Trend & Seasonal Introduction This module forecasts seasonal series with upward or downward trends using the Holt -Winters exponential smoothing algorithm. Two seasonal adjustment techniques are available: additive and multiplicative. Additive Seasonality Given observations X 1
- In this section we implement label smoothing in Microsoft Excel. We know that cross-entropy loss equals: Great, and from section-2, What we have essentially done, is that we take the exponential of the logits, to get exp (cat) and exp (dog) from logit (cat) and logit (dog). Next, we take get the sum (exp) by adding exp (cat) and exp (dog) along the rows. Finally, we get prob (cat) by.
- Which, in Excel, translates to: =EXP(number) Fitting a Power Function to Data. A power function curve can be fit to data using LINEST in much the same way that we do it for an exponential function. A power function has the form: Again, we can linearize it by taking the base 10 log of both sides of the equation to obtain: With the equation in this form, the LINEST function to return b and.
- Exponential Smoothing is a time series forecasting method for univariate data, that can be extended to support data which has trend & seasonal components. Exponential smoothing forecasting methods are similar in that a prediction is a weighted sum of past observations, but the model explicitly uses an exponentially decreasing weight for past observations. Specifically, past observations are.

Exponential smoothing methods assign exponentially decreasing weights for past observations. The more recent the observation is obtained, the higher weight would be assigned. For example, it is reasonable to attach larger weights to observations from last month than to observations from 12 months ago. Exponential smoothing Weights from Past to Now . This article will illustrate how to build. Exponential Smoothing that adds support for trends in the univariate time series. It requires beta (b) along with alpha (a) beta (b) parameter - smoothing factor controls the changes in trend influence rate to decay exponentially (value between 0 and 1.) * Additive Trend: Double Exponential Smoothing with a linear trend. * Multiplicative Trend: Double Exponential Smoothing with an exponential. Introduction Exponential smoothing methods The simplest exponential smoothing method is the single smoothing (SES) method where only one parameter needs to be estimated Holt's method makes use of two different parameters and allows forecasting for series with trend. Holt-Winters' method involves three smoothing parameters to smooth the data. Simple Seasonal Exponential Smoothing. The remaining sections of this chapter omit the use of regression-based solutions to seasonal time series and focus on smoothing solutions. The Holt method for dealing with trended, but not seasonal, time series employs two smoothing constants, one for the series' level and one for its trend or slope

- Exponential smoothing refers to the use of an exponentially weighted moving average (EWMA) to smooth a time series. If you have some time series x t, you can define a new time series s t that is a smoothed version of x t. s t = α x t + (1 − α) s t − 1. Here's a plot of a stationary time series, like the previous example, along with a couple of smoothed versions. Notice how the.
- Exponential Smoothing - Trend Introduction This module forecasts series with upward or downward trends. Three techniques are available: least squares trend, double smoothing, and Holt's linear trend algorithm. Least Squares Trend Least squares trend computes a straight-line trend equation through the data using standard least square
- ation of Optimum Smoothing Constant of Single Exponential Smoothing Method: A Case Study 3. Materials and Methods 3.1 Sample and measuring technique The study involves the use of various methods for deter
- Tutorial : Double Exponential Smoothing Holt dan Forecasting. Dalam artikel artikel sebelumnya telah dibahas tentang Single Exponential Smoothing, oleh karena itu pada artikel kali akan dibahas secara sederhana tentang Double Exponential Smoothing Holt. Double Exponential Smoothing Holt sering digunakan untuk data deret waktu dengan pola tren

- Exponential Smoothing Calculator More about the Exponential Smoothing Forecasts so you can get a better understanding of the outcome that will be provided by this solver. The idea behind Exponential Smoothing for making forecasts consists of estimating the data value of certain period based on the previous data value as well as the previous forecast, so that to attempt to correct for the.
- Exponential Smoothing Excel Template Paraffinic Giles always stellify his symmetalism if Uri is Salishan or embank simperingly. Momently dumpier, Jef decimate cueist and shag virescence. Is Costa always inadaptable and self-explanatory when analogising some Erastus very dead and stammeringly? Discuss how to the function uses cookies again display the sheet. Out of your cds and excel has a.
- It is straightforward to perform seasonal adjustment and fit exponential smoothing models using a spreadsheet program such as Excel. The screen images and charts below are taken from a spreadsheet which has been set up to illustrate multiplicative seasonal adjustment and linear exponential smoothing on the Outboard Marine data from your textbook
- Exponential Smoothing/Pemulusan Eksponensial dengan excel. Input Range - Masukkan data sel untuk range data yang ingin Anda menganalisis. Range ini harus berisi satu kolom atau baris dengan empat atau lebih sel data. Damping factor -Masukkan Faktor Damping yang ingin Anda gunakan sebagai konstanta eksponensial

You can make your own simple exponential smoothing in Excel or in Python . About the author. Nicolas Vandeput is a supply chain data scientist specialized in demand forecasting and inventory. Adjusted Exponential Smoothing Forecasting Method • A method that uses measurable, historical data observations, to make forecasts by calculating the weighted average of the current period's actual value and forecast, with a trend adjustment added in. When to Use the Method • Preferred Scenario: - When a trend is present • Good Scenario: - When there's a cyclical or seasonal.

Exponential smoothing of time series. 4.0. 1 Rating . 9 Downloads. Updated 23 Jan 2012. View Version History. × Version History. Download. 23 Jan 2012: 1.1.0.0: Updated title. Download. 23 Jan 2012: 1.0.0.0: View License. × License. Follow; Download. Overview; Functions; Y = EXPSMOOTH( X, FS, TAU ) Given input sequence X (column vector), sampled at FS Hertz, returns exponentially smoothed. The tutorial explains how to use Excel FORECAST and other related functions with formula examples. In Microsoft Excel, there are several functions that can help you create linear and exponential smoothing forecasts based on historical data such as sales, budgets, cash flows, stock prices, and the like Exponential smoothing demo. In my experience users of exponential smoothing have often limited transparency in how the various smoothing parameters interact. I built this small demo to illustrate how the different smoothing parameters and exponential smoothing components interact. You can choose between some simulated and some real time series. The Single Exponential Smoothing model used for the fit is: Ŷ 1 = Y 1. Ŷ t+1 = αY t + (1 - α)Ŷ t. where. Y t = the value of the data at time t. Ŷ = the fitted value at time t. α = weighting constant. This help page describes how to perform the Single Exponential Smoothing time series analysis using the SPC for Excel software with the. This is the second part of the Average True Range (ATR) Excel tutorial. In the first part we have calculated ATR using the simple moving average method. Now we will calculate ATR using two other popular methods - exponential moving average and Wilder's smoothing method

Excel has an exponential smoothing. I have a graph I'd like to smooth, however the Mac version doesn't seem to have this feature. Is there a way I can smooth the chart - either as a chart feature or by using a formula in additional cells to smooth the chart:? excel macos charts smoothing excel-2016. Share. Follow asked Feb 25 '16 at 18:13. mikemaccana mikemaccana. 81.8k 73 73 gold badges 317. def exp_smoothing_trend(ts,extra_periods=1, alpha=0.4, beta=0.4, plot=False): This function calculates a forecast with an exponential smoothing with trend method. Inputs - ts: the historical values (a list, a numpy array or a pandas series) - extra_perios: the number of data points that you want to forecast - alpha: the level parameter - beta: the trend parameter - plot: if True the. Exponential Smoothing with a Damped Multiplicative Trend Abstract Multiplicative trend exponential smoothing has received very little attention in the literature. It involves modelling the local slope by smoothing successive ratios of the local level, and this leads to a forecast function that is the product of level and growth rate. By contrast, the popular Holt method uses an additive trend. Three exponential smoothing techniques are examined in this part of the study: single exponential smoothing, Brown's double exponential smoothing, and Holt's two-parameter exponential smoothing. The one-period-ahead forecast for single exponential smoothing can be written as 1 ˆ y T+ = y T + (1 - y) ˆ T (1) chosen in this case. Again, a. Now that we've covered simple exponential smoothing, Holt's method, and double exponential smoothing, we'll combine some of these features to develop the Holt-Winter's Model also known as triple exponential smoothing. Notice that we dropped the trend term ($\hat{b}$) when we moved from Holt's method to the double exponential smoothing example. That is re-introduced here, just as it was used in.

Time Series with Trend: Double Exponential Smoothing. h2. What Is Double Exponential Smoothing? like regular exponential smoothing, except includes a component to pick up trends. Time Series with Trend: Double Exponential Smoothing. Formula . Ft = Unadjusted forecast (before trend) Tt = Estimated trend ; AFt = Trend-adjusted forecast; Ft = a* At-1 + (1- a) * (Ft-1 + Tt-1) Tt = b* (At-1-Ft-1. * Exponential Smoothing Forecaset with a = *.3. h2. What is Exponential Smoothing? A type of weighted moving averaging model; Part of many forecasting packages; ideal for developing forecasts of lots of smaller items; Needs only three numbers: Ft-1 = Forecast for the period before . current time period t. At-1 = Actual demand for the period . before current time period t. a = Weight between 0 and. Double Exponential Smoothing lebih akurat dengan metode Triple Exponential Smoothing dengan nilai α = 0,5 dengan MAPE = 15,262 % Kata kunci : forecasting, timelag, DES (Double Exponential Smoothing), TES (Triple Exponential Smoothing). MAPE. Perbandingan metode 1. Pendahuluan Dalam membandingkan tingkat akurasi peramalan khususnya pada penjualan di Toko Utama, dapat sangat mudah dilakukan. METODE EXPONENTIAL SMOOTHING HOLT-WINTERS DAN ARIMA Skripsi disusun sebagai salah satu syarat untuk memperoleh gelar Sarjana Sains Program Studi Matematika oleh Tias Safitri 4111412010 JURUSAN MATEMATIKA FAKULTAS MATEMATIKA DAN ILMU PENGETAHUAN ALAM UNIVERSITAS NEGERI SEMARANG 2016 . ii . iii . iv MOTTO DAN PERSEMBAHAN MOTTO Sesungguhnya bersama kesulitan itu ada kemudahan (QS. Al-Insyirah: 6. Exponential smoothing is a term for a set of straightforward forecasting procedures that apply self-correction. Each forecast comprises two components. It's a weighted average of the prior.

* Keywords: Double Exponential Smoothing, Forecasting, Type of Child Violence INTISARI Tingginya kasus kekerasan pada anak dewasa ini semakin meningkat*. Diantara kasus kekerasan pada anak yaitu penyiksaan fisik, pelecehan seksual, dan penelantaran. Setiap tahun kekerasan pada anak semakin meningkat dengan pola perilaku yang berbeda-beda. Berbagai upaya dilakukan pemerintah untuk mengkampanyekan. iv Predictive Analytics: Microsoft Excel Smoothing Versus Tracking.