scholarly journals Perbandingan Metode Single Exponential Smoothing dan Metode Holt untuk Prediksi Kasus COVID-19 di Indonesia

2020 ◽  
Vol 12 (2) ◽  
pp. 89-94
Author(s):  
Nur Hijrah As Salam Al Ihsan ◽  
Hanifah Hanun Dzakiyah ◽  
Febri Liantoni
Keyword(s):  
Disaster Management ◽  
Exponential Smoothing ◽  
Smoothing Method ◽  
Management Agency ◽  
Double Exponential ◽  
Double Exponential Smoothing ◽  
The Right ◽  
National Disaster ◽  
Exponential Smoothing Method ◽  
Single Exponential

Coronavirus disease (COVID-19) was first discovered in December 2019 in Wuhan, China, and spread so quickly into a pandemic. This outbreak has spread to 24 other countries, including Indonesia. Its spread is very fast, so a co-19 prediction study is needed to be able to make the right policy. To be able to predict the number of COVID-19 cases can be done with the Forecasting Technique. The purpose of this study is to forecast and compare Single Exponential Smoothing and Double Exponential Smoothing ¬ against the number of COVID-19 cases in Indonesia. The results of this study can be used as consideration for policymaking in dealing with the spread of COVID-19. Distribution predictions are based on data released by the Indonesian National Disaster Management Agency (BNPB) in the first 100 days of COVID-19 deployment. The results of this study are the Double Exponential Smoothing method is more accurate than the Single Exponential Smoothing method because the forecasting results show an increase from the previous data. And the percentage of errors (MAPE) obtained is significantly smaller.

scholarly journals Sistem Informasi Peramalan Persediaan Barang Menggunakan Metode SES Dan DES

2019 ◽  
Vol 4 (1) ◽  
pp. 1-6
Author(s):  
Ratih Yulia Hayuningtyas
Keyword(s):  
Medical Equipment ◽  
Exponential Smoothing ◽  
Smoothing Method ◽  
Equal Weight ◽  
Mean Square ◽  
Double Exponential ◽  
Forecasting System ◽  
Double Exponential Smoothing ◽  
Exponential Smoothing Method ◽  
Single Exponential

Abstract: Sales is an activity in selling products that provide information about inventory. Arga Medical is a shop engaged in the sale of medical equipment, many of sales transactions in the Arga Medical will affect the inventory. Problems in the Arga Medical is predicting many of product that must available for the next month. Therefore this research makes inventory information forecasting system using Single Exponential Smoothing and Double Exponential Smoothing method. This inventory forecasting information system will result a inventory forecasting for next month. Single Exponential Smoothing Method gives equal weight to each data while Double Exponential Smoothing method is smoothing twice. The Data used in this research is the sales data during 2016. Both of these methods resulted inventory forecasting in the next month is Januari 2017 of 52 with Single Exponential Smoothing and 60 with Double Exponential Smoothing. Each method has a Mean Square Error value the smallest error value is the best method for forecasting inventory. Keywords: Forecasting, Inventory, Single Exponential Smoothing, Double Exponential Smoothing.

scholarly journals Implementasi Metode Penghalusan Ekponensial Tunggal Dalam Prediksi Penjualan Buku

2021 ◽  
Vol 9 (2) ◽  
pp. 1
Author(s):  
Heri Setyawan ◽  
Sri Hariyati Fitriasih ◽  
Retno Tri Vulandari
Keyword(s):  
Mean Squared Error ◽  
Exponential Smoothing ◽  
Smoothing Method ◽  
Squared Error ◽  
Double Exponential ◽  
Double Exponential Smoothing ◽  
Product Sales ◽  
Exponential Smoothing Method ◽  
The Relationship ◽  
Single Exponential

The prediction of the quantity of product sales in the future is intended to control the amount of existing product stock, so that product shortages or excess stock can be minimized. When the quantity of sales can be predicted accurately, the fulfillment of consumer demand can be sought on time and the cooperation of the store with the relationship is maintained well so that the store can avoid losing both sales and consumers. The purpose of this study is to compare the effectiveness of the use of the Single Exponential Smoothing method and methods Double Exponential Smoothing with a smoothing parameter value a = 0.5 for forecasting sales by comparing the error values in the two methods using the Mean Squared Error (MSE) method, the MSE results of the Single Exponential Smoothing method is 4967.75 while the MSE Double Exponential Smoothing is 5113.03. Thus, the Single Exponential Smoothing method is more accurate than Double Exponential Smoothing in calculating book sales forecasting because it has a low MSE value.

scholarly journals Identification COVID-19 Cases in Indonesia with The Double Exponential Smoothing Method

2020 ◽  
Vol 6 (1) ◽  
pp. 66-75 ◽  
Author(s):  
Sri Harini
Keyword(s):  
Arima Model ◽  
Exponential Smoothing ◽  
Smoothing Method ◽  
Estimated Parameters ◽  
Double Exponential ◽  
Time Series Approach ◽  
Smoothing Parameters ◽  
Double Exponential Smoothing ◽  
National Disaster ◽  
Exponential Smoothing Method

The time-series approach is a method used to analyze a series of data in a time sequence to estimate the value of a series in the future. This article will identification the COVID-19 case model in Indonesia using the Double Exponential Smoothing Method. The Double Exponential Smoothing method is one method that can be used to optimize the estimation of the ARIMA model with smoothing parameters α. The data used is sourced from the National Disaster Management Agency which was released starting March 2, 2020. Based on the results of PACF, ACF, and estimated parameters of the ARIMA model in the Covid-19 case in Indonesia following the ARIMA model (0,1,1).

scholarly journals Forecasting Of Criminality Problems Using Double Exponential Smoothing Method

Academia Open ◽  
2021 ◽  
Vol 4 ◽  
Author(s):  
Fatikhul Ikhsan ◽  
Sumarno
Keyword(s):  
Social Action ◽  
Police Officers ◽  
Exponential Smoothing ◽  
Smoothing Method ◽  
Legal Norms ◽  
The Public ◽  
Police Station ◽  
Double Exponential ◽  
Double Exponential Smoothing ◽  
Exponential Smoothing Method

Crime is a form of social action that violates legal norms relating to acts of seizing property rights of others, disturbing public order and peace, and killing one or a group of people. This has always been a concern for residents in various places in the Ngoro sub-district, therefore this information system was created to help police officers to find out where crimes have occurred. This information sfystem was created to predict the area in Ngoro sub-district using the Double Exponential Smoothing method. So that this system can predict which areas in the next month there will be no crime, and can assist the public in reporting the occurrence of criminal acts without having to go to the police station first. The Double Exponential Smoothing method was chosen by the author because this method can be used. The data used is data on theft of crime from 2017 – 2019. The results of forecasting in one village in Ngoro sub-district such as Manduro are 0.07426431198 if rounded up to 0.1 which is categorized as low crime and has a MAPE value of 7.94%. Based on the MAPE value of the forecasting results, it can be concluded that a good constant is between 0.1 – 0.3.

scholarly journals Komparasi Metode Peramalan Jumlah Permintaan Kamar Hotel

2019 ◽  
Vol 9 (2) ◽  
Author(s):  
Rendra Gustriansyah ◽  
Wilza Nadia ◽  
Mitha Sofiana
Keyword(s):  
Moving Average ◽  
Exponential Smoothing ◽  
Standard Type ◽  
The Public ◽  
Forecasting Methods ◽  
Forecasting Method ◽  
Double Exponential ◽  
Double Exponential Smoothing ◽  
Exponential Smoothing Method ◽  
Single Exponential

<p class="SammaryHeader" align="center"><strong><em>Abstract</em></strong></p><p><em>Hotel is  a type of accommodation that uses most or all of the buildings to provide lodging, dining and drinking services, and other services for the public, which are managed commercially so that each hotel will strive to optimize its functions in order to obtain maximum profits. One such effort is to have the ability to forecast the number of requests for hotel rooms in the coming period. Therefore, this study aims to forecast the number of requests for hotel rooms in the future by using five forecasting methods, namely linear regression, single moving average, double moving average, single exponential smoothing, and double exponential smoothing, as well as to compare forecasting results with these five methods so that the best forecasting method is obtained. The data used in this study is data on the number of requests for standard type rooms from January to November in 2018, which were obtained from the Bestskip hotel in Palembang. The results showed that the single exponential smoothing method was the best forecasting method for data patterns as in this study because it produced the smallest MAPE value of 41.2%.</em></p><p><strong><em>Keywords</em></strong><em>: forecasting, linier regression, moving average, exponential smoothing.</em></p><p align="center"><strong><em>Abstrak</em></strong></p><p><em>Hotel merupakan jenis akomodasi yang mempergunakan sebagian besar atau seluruh bangunan untuk menyediakan jasa penginapan, makan dan minum serta jasa lainnya bagi umum, yang dikelola secara komersial, sehingga setiap hotel akan berupaya untuk mengoptimalkan fungsinya agar memperoleh keuntungan maksimum. Salah satu upaya tersebut adalah memiliki kemampuan untuk meramalkan jumlah permintaan terhadap kamar hotel pada periode mendatang. Oleh karena itu, penelitian ini bertujuan untuk meramalkan jumlah permintaan terhadap kamar hotel di  masa mendatang dengan menggunakan lima metode peramalan, yaitu regresi linier, single moving average, double moving average, single exponential smoothing, dan double exponential smoothing, serta untuk mengetahui perbandingan hasil peramalan dengan kelima metode tersebut sehingga diperoleh metode peramalan terbaik. Adapun data yang digunakan dalam penelitian ini merupakan data jumlah permintaan kamar tipe standar dari bulan Januari hingga November tahun 2018, yang diperoleh dari hotel Bestskip Palembang. Hasil penelitian menunjukkan bahwa metode single exponential smoothing merupakan metode peramalan terbaik untuk pola data seperti pada penelitian ini karena menghasilkan nilai MAPE paling kecil sebesar 41.2%.</em></p><strong><em>Kata kunci</em></strong><em>: peramalan, regeresi linier, moving average, exponential smoothing.</em>

scholarly journals Forecasting production,consumption and the food gap of rice crop in Iraq using Exponential Smoothing method

2021 ◽  
Vol 8 (2) ◽  
Author(s):  
Iman K, Mustafa ◽  
Osamah.K. Jbara
Keyword(s):  
Exponential Smoothing ◽  
Smoothing Method ◽  
The Self ◽  
Rice Crop ◽  
Factors Affecting ◽  
Production Ratio ◽  
Self Sufficiency ◽  
Double Exponential Smoothing ◽  
Exponential Smoothing Method ◽  
Single Exponential

"The aim of this research is to predict the production, consumption and food gap of the rice crop in Iraq, as well as the economic factors that affect the self-sufficiency ratio and the quantity of imports with the time series (2015-1980). Based on the statistical program (Minitab & SPSS) Is the Exponential Smoothing method for Forecasting the production, consumption, and nutritional gap of the rice crop. Two types of single and double (2016-2025) was the single Exponential Smoothing method for having the lowest MSE value of (11450.4) . As for the consumption of the rice yield for the period (2025-2016), the double Exponential Smoothing method was the most accurate (MSE), which is 87100.7. As for the food gap, the single Exponential Smoothing is the best predictor for the same period in terms of the lowest value (MSE) 84100.1. The self-sufficiency ratio was affected by five factors (cultivated area, Imports, available for consumption, import / production ratio, the dummy variable representing years of blockade), and Factors affecting the quantity of imports (rice production,available for consumption, border prices, the number of the population Al- Muthanna University All rights reserved"

scholarly journals Implementasi Sistem Informasi Prediksi Hasil Penjualan Perangkat Komputer Menggunakan Metode Double Exponential Smoothing

2020 ◽  
Vol 4 (3) ◽  
pp. 806
Author(s):  
Nurul Adha Oktarini Saputri ◽  
Nurul Huda
Keyword(s):  
Exponential Smoothing ◽  
Sales Forecast ◽  
Double Exponential ◽  
Sales Prediction ◽  
The Future ◽  
Time Series Method ◽  
Past Data ◽  
Double Exponential Smoothing ◽  
The Right ◽  
Exponential Smoothing Method

Prediction is an activity to predict a situation that will occur in the future by passing tests in the past. One way to get sales information in the future is to make sales forecasting. This sales forecast uses the Double Exponential Smoothing method because this method predicts by smoothing or smoothing past data by taking an average of several years to estimate the value of the coming year and this method uses the time series method. The results of this study are the right sales prediction information system, in order to determine the existing inventory of goods in accordance with the demand (demand) so that there is no overstock or lack of inventory in the future

scholarly journals Forecasting the Number of Coronavirus (COVID-19) Cases in Ethiopia Using Exponential Smoothing Times Series Model

2020 ◽  
Author(s):  
Teshome Hailemeskel Abebe
Keyword(s):  
Time Series Data ◽  
Exponential Smoothing ◽  
Series Data ◽  
Smoothing Methods ◽  
Times Series ◽  
Double Exponential ◽  
Forecasting Performance ◽  
Double Exponential Smoothing ◽  
The Right ◽  
Exponential Smoothing Method

AbstractThe main objective of this study is to forecast COVID-19 case in Ethiopiausing the best-fitted model. The time series data of COVID-19 case in Ethiopia from March 14, 2020 to June 05, 2020 were used.To this end, exponential growth, single exponential smoothing method, and doubleexponential smoothing methodwere used. To evaluate the forecasting performance of the model, root mean sum of square error was used. The study showed that double exponential smoothing methods was appropriate in forecasting the future number ofCOVID-19 cases in Ethiopia as dictated by lowest value of root mean sum of square error. The forecasting model shows that the number of coronavirus cases in Ethiopia grows exponentially. The finding of the results would help the concerned stakeholders to make the right decisions based on the information given on forecasts.

Sign in / Sign up

Export Citation Format

Share Document