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

"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"

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PERBANDINGAN METODE SINGLE EXPONENTIAL SMOOTHING DAN MOVING AVERAGE PADA PERAMALAN PENJUALAN PRODUK MINYAK GORENG DI PT TUNAS BARU LAMPUNG

JURNAL REKAYASA SISTEM INDUSTRI ◽

10.33884/jrsi.v6i2.3694 ◽

2021 ◽

Vol 6 (2) ◽

pp. 101

Author(s):

Niken Chaerunnisa ◽

Ade Momon

Keyword(s):

Moving Average ◽

Exponential Smoothing ◽

Smoothing Method ◽

Oil Products ◽

Cooking Oil ◽

Forecasting Method ◽

Double Exponential Smoothing ◽

Product Sales ◽

Exponential Smoothing Method ◽

Single Exponential

PT Tunas Baru Lampung is a company that produces palm cooking oil products under the Rose Brand brand. In product sales, companies sometimes experience ups and downs. Based on the sales data from Rose Brand Cooking Oil, the size of 1 L has fluctuated or in each period it changes and is not always boarding. Even though product sales are one of the important things to be evaluated from time to time on an ongoing basis. To predict future sales, forecasting is done. The forecasting method used is Double Exponential Smoothing and Moving Average. The method of accuracy will be compared using MSE, MAD, and MAPE. The results showed a comparison of the accuracy and the smallest error value in each method. By using the weight values 0.1, 0.3, 0.4, 0.5, 0.6, 0.7, and 0.8 on the Single Exponential Smoothing method the weight value is 0.8 or α = 0.8, namely MSE of 250,570,764.80, MAD of 12,922.32 and MAPE of 33.55 Then, using the movement value n = 3 in the Moving Average method has an accuracy of 438,980,942.75 MSE, 18,142.14 MAD, and 41.37 MAPE. After comparing the accuracy of the two methods, the Single Exponential Smoothing method is the best method to predict sales of Rose Brand 1 L Cooking Oil products.

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Sistem Informasi Peramalan Persediaan Barang Menggunakan Metode SES Dan DES

Indonesian Journal on Software Engineering (IJSE) ◽

10.31294/ijse.v4i1.6228 ◽

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.

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Implementasi Metode Penghalusan Ekponensial Tunggal Dalam Prediksi Penjualan Buku

Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN) ◽

10.30646/tikomsin.v9i2.539 ◽

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.

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

Jurnal ULTIMATICS ◽

10.31937/ti.v12i2.1689 ◽

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.

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The Prediction Of Export Product Prices With Holt’s Double Exponential Smoothing Method

2020 3rd International Conference on Computer and Informatics Engineering (IC2IE) ◽

10.1109/ic2ie50715.2020.9274679 ◽

2020 ◽

Author(s):

Hata Maulana ◽

Ulfa Mulyantika

Keyword(s):

Exponential Smoothing ◽

Smoothing Method ◽

Double Exponential ◽

Double Exponential Smoothing ◽

Exponential Smoothing Method ◽

Export Product

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Forecasting of Groundwater Tax Revenue Using Single Exponential Smoothing Method

E3S Web of Conferences ◽

10.1051/e3sconf/201912523006 ◽

2019 ◽

Vol 125 ◽

pp. 23006

Author(s):

Dyna Marisa Khairina ◽

Aqib Muaddam ◽

Septya Maharani ◽

Heliza Rahmania

Keyword(s):

Reference Value ◽

Exponential Smoothing ◽

Smoothing Method ◽

Percentage Error ◽

Tax Revenue ◽

Regional Office ◽

Forecasting Error ◽

The Government ◽

Exponential Smoothing Method ◽

Single Exponential

Setting the target of groundwater tax revenues for the next year is an important thing for Kutai Kartanegara Regional Office of Revenue to maximize the regional income and accelerate regional development. Process of setting the target of groundwater tax revenue for the next year still using estimation only and not using a mathematical calculation method that can generate target reference value. If the realization of groundwater tax revenue is not approaching the target, the implementation of development in the Government of Kutai Kartanegara can be disrupted. The mathematical method commonly used to predict revenue value is the Single Exponential Smoothing (SES) method, which uses alpha constant value which is randomly selected for the calculation process. Forecasting of groundwater tax revenue for 2018 using groundwater tax revenue data from 2013 to 2017. Single Exponential Smoothing method using alpha constant value consists of 0.1, 0.2, 0.3, 0.4 and 0.5. The forecasting error value of each alpha value is calculated using the Mean Absolute Percentage Error (MAPE) method. The best result is forecasting using alpha value 0.1 with MAPE error value was 45.868 and the best forecasting value of groundwater tax for 2018 is Rp 443.904.600,7192.

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Single exponential smoothing method to predict sales multiple products

Journal of Physics Conference Series ◽

10.1088/1742-6596/1175/1/012036 ◽

2019 ◽

Vol 1175 ◽

pp. 012036

Author(s):

R Gustriansyah ◽

N Suhandi ◽

F Antony ◽

A Sanmorino

Keyword(s):

Exponential Smoothing ◽

Smoothing Method ◽

Multiple Products ◽

Exponential Smoothing Method ◽

Single Exponential

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Forecasting Of Criminality Problems Using Double Exponential Smoothing Method

Academia Open ◽

10.21070/acopen.4.2021.2003 ◽

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.

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Komparasi Metode Peramalan Jumlah Permintaan Kamar Hotel

Jurnal Ilmiah Informatika Global ◽

10.36982/jig.v9i2.563 ◽

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

AbstractHotel 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%.Keywords: forecasting, linier regression, moving average, exponential smoothing.AbstrakHotel 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%.Kata kunci: peramalan, regeresi linier, moving average, exponential smoothing.

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