scholarly journals Comparison of Exponential Smoothing Methods for Forecasting Marine Fish Production in Pekalongan Waters, Central Java

2021 ◽  
Vol 934 (1) ◽  
pp. 012016
Author(s):  
A Pamungkas ◽  
R Puspasari ◽  
A Nurfiarini ◽  
R Zulkarnain ◽  
W Waryanto
Keyword(s):  
Marine Fish ◽  
Exponential Smoothing ◽  
Percentage Error ◽  
Production Data ◽  
Fish Production ◽  
Smoothing Methods ◽  
Central Java ◽  
Double Exponential Smoothing ◽  
Trial And Error Method ◽  
Exponential Smoothing Method

Abstract Pekalongan waters, a part of the Java Sea, has potency to develop marine fisheries sector to increase regional income and community livelihoods. The fluctuation of marine fish production every year requires serious attention in planning and policy strategies for the utilization of the fishery resources. Time series fish production data can be used to predict fish production in the following years through the forecasting process. The data used in this study is fish production data from Pekalongan Fishing Port, Central Java, from January 2011 to December 2020. The method used is data exponential smoothing by comparing three exponential smoothing methods consisting of single/simple exponential smoothing, double exponential smoothing and Holt-Winters’ exponential smoothing. The criterion that used to measure the forecasting performance is the mean absolute percentage error (MAPE) value. The smaller MAPE value shows the better the forecasting result. The smallest MAPE value is obtained by finding the optimal smoothing constant value which is usually calculated using the trial and error method. However, in this study, the constant value was calculated using the add-in solver approach in Microsoft Excel. The forecasting results obtained show that forecasting using the Holt Winter Exponential Smoothing method is reasonable with a MAPE value of 37.878.

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.

Implementasi Metode Double Exponential Smoothing dalam Memprediksi Pertambahan Jumlah Penduduk di Wilayah Kabupaten Karawang

2020 ◽  
Vol 12 (2) ◽  
pp. 95-103
Author(s):  
Andini Diyah Pramesti ◽  
Mohamad Jajuli ◽  
Betha Nurina Sari
Keyword(s):  
Population Distribution ◽  
Exponential Smoothing ◽  
Smoothing Method ◽  
Percentage Error ◽  
Population Census ◽  
Double Exponential ◽  
Double Exponential Smoothing ◽  
Exponential Smoothing Method ◽  
Better Than ◽  
Population Numbers

The density and uneven distribution of the population in each area must be considered because it will cause problems such as the emergence of uninhabitable slums, environmental degradation, security disturbances, and other population problems. In the data obtained from the 2010 population census based on the level of population distribution in Karawang District, the area of West Karawang, East Karawang, Rengasdengklok, Telukjambe Timur, Klari, Cikampek and Kotabaru are zone 1 regions which are the densest zone with a population of 76,337 people up to 155,471 inhabitants. This research predicts / forecasting population growth in the 7 most populated areas for the next 1 year using Double Exponential Smoothing Brown and Holt methods. This study uses Mean Absolute Percentage Error (MAPE) to evaluate the performance of the double exponential smoothing method in predicting per-additional population numbers. Forecasting results from the two methods place the Districts of East Telukjambe, Cikampek, Kotabaru, East Karawang, and Rengasdengklok in 2020 to remain in zone 1 with a range of 76,337 people to 155,471 inhabitants. Whereas in the Districts of Klari and West Karawang are outside the range in zone 1 because both districts have more population than the range in zone 1. From the results of MAPE both methods are found that 6 out of 7 districts in the method Holt's double exponential smoothing produces a smaller MAPE value compared to the MAPE value generated from Brown's double exponential smoothing method. It was concluded that in this study the Holt double exponential smoothing method was better than Brown's double exponential smoothing method.

scholarly journals Prediction Of Drug Sales Using Methods Forecasting Double Exponential Smoothing (Case Study : Hospital Pharmacy of Condong Catur)

Telematika ◽  
2021 ◽  
Vol 18 (1) ◽  
pp. 106
Author(s):  
Annesa Maya Sabarina ◽  
Heru Cahya Rustamaji ◽  
Hidayatulah Himawan
Keyword(s):  
Exponential Smoothing ◽  
Smoothing Method ◽  
Test Results ◽  
Drug Sale ◽  
Smoothing Methods ◽  
Double Exponential ◽  
Double Exponential Smoothing ◽  
Exponential Smoothing Method ◽  
Study Hospital

Purpose: Knowing the best alpha value from the data for each type of drug with various alpha parameters in the Double Exponential Smoothing Method and knowing the prediction results on each type of drug data at the Condong Catur Hospital pharmacy.Design/methodology/approach: Applying the Double Exponential Smoothing method with alpha parameters 0.1; 0.2; 0.3; 0.4; 0.5; 0.6; 0.7; 0.8; 0.9Findings/result: The test results on a system built using test data show that the double exponential smoothing method provides accuracy below 20% by producing a different Alpha (α) for each type of drug because the trend patterns in each drug sale are different at the Pharmacy at the Condong Catur Hospital. .Originality/value/state of the art: Based on previous research, this study has similar characteristics such as themes, parameters and methods used. Previous researchers used smoothing methods such as Double Exponential Smoothing in predicting stock / sales of goods 

scholarly journals Aplikasi Peramalan Jumlah Siswa Sekolah Dasar di Kabupaten Tanah Laut Menggunakan Metode Holt’s Double Exponential Smoothing

2018 ◽  
Vol 7 (2) ◽  
pp. 64-69
Author(s):  
Nora Apriliyani ◽  
Herfia Rhomadhona ◽  
Jaka Permadi
Keyword(s):  
Exponential Smoothing ◽  
Learning Processes ◽  
Flow Diagram ◽  
Percentage Error ◽  
School Students ◽  
Double Exponential ◽  
Double Exponential Smoothing ◽  
Entity Relationship ◽  
Entity Relationship Diagram ◽  
Exponential Smoothing Method

Learning processes in the elementary schools at Tanah Laut District is affected by the number of students. Through the number of students can be predicted how much the need of additional teachers, rooms, textbooks and learning medias that support learning processes in the schools. In other words, the infrastructure of the schools can be predicted by the number of students that is registered in Tanah Laut District. The research use Holt’s Double Exponential Smoothing method to predicting the number of the prospective students in Tanah Laut District. Mean Absolute Percentage Error (MAPE) technique is used to calculate the percentage of error from the forecasting’s result. The system is designed by Entity Relationship Diagram (ERD) and Data Flow Diagram (DFD). The forecasting that have been done said that the number of Tanah Laut’s elementary school students at 2018 is 35655 students, with the value of MAPE is about 0.77%, a = 0.77 and ß = 0.8.

scholarly journals Prediksi Penjualan Kertas Menggunakan Metode Double Exponential Smoothing

2021 ◽  
Vol 9 (1) ◽  
pp. 60
Author(s):  
Erinsyah Aditya Nugroho Putro ◽  
Elistya Rimawati ◽  
Retno Tri Vulandari
Keyword(s):  
Raw Materials ◽  
Exponential Smoothing ◽  
Economic Losses ◽  
Percentage Error ◽  
Business Owner ◽  
Know How ◽  
Goods And Services ◽  
Double Exponential ◽  
Double Exponential Smoothing ◽  
Exponential Smoothing Method

One of the important thing in business is the inventory of goods and services. Business goal can be reached when business owner know how the number of their inventory. Printing business is using forecasting model in their purchasing raw materials to estimate and calculate their selling prediction. That model is used to minimize economic losses when the costumer canceled order because paper was ran out and to prevent paper damage does not occur date to storage that to long. Double Exponential Smoothing method is used in this research to predict the sales of Paper A and HVS A3+ paper and calculates the prediction error with MAPE (Mean Absolute Percentage Error). This study aims to make an accurate forecasting application. The prediction results from application are in the form of prediction calculations for sales in the following month which will be used to optimize the purchase of paper to be sold. In applying the research results of Paper A and HVS A3 +, the best alpha was obtained in the 12th period, namely 0.3 and 0.6 with a MAPE error of 12% and 18% and an accuracy rate of 88% and 82% where the alpha was used to predict period 13 and produces a forecast value of 446 for Paper A and 474 for HVS A3 +

Forecasting Bitcoin using Double Exponential Smoothing Method Based on Mean Absolute Percentage Error

2020 ◽  
Vol 4 (2) ◽  
pp. 91
Author(s):  
Febri Liantoni ◽  
Arif Agusti
Keyword(s):  
Exponential Smoothing ◽  
Smoothing Method ◽  
Mean Absolute Percentage Error ◽  
Percentage Error ◽  
Business World ◽  
Absolute Percentage Error ◽  
A Value ◽  
Double Exponential ◽  
Double Exponential Smoothing ◽  
Exponential Smoothing Method

Abstract— After being introduced in 2008, the rise in the price of bitcoin and the popularity of other cryptocurrencies triggered a growing discussion about how much energy was consumed during the production of this currency. Making cryptocurrency the most expensive and most popular, both the business world and the research community have begun to study the devel-opment of bitcoin. In this study bitcoin price predictions are performed using the double exponential smoothing method based on the mean absolute percentage error (MAPE). The MAPE value is used to find the best alpha (α) parameter as the basis for bitcoin price forecasting. The dataset used is the price of bitcoin from 2017 to 2019. The dataset was obtained from www.cryptocompare.com. As for the value of the alpha parameter (α), using a value of 0.1 to 0.9. Based on the test results using the double exponential smoothing method obtained the smallest MAPE value of 2.89%, with the best alpha (α) at 0.9. The prediction is done to see the price of bitcoin on January 1, 2020. The error rate generated on the predicted price of bitcoin uses an amount of 0.0373%. This shows that the system built can be used as a support for decision making when trading bitcoin.

scholarly journals FORECASTING THE CONSUMER PRICE INDEX IN YOGYAKARTA BY USING THE DOUBLE EXPONENTIAL SMOOTHING METHOD

2021 ◽  
Vol 2 (1) ◽  
pp. 1-7
Author(s):  
Syintya Febriyanti ◽  
Wahyu Aji Pradana ◽  
Juliana Saputra Muhammad ◽  
Edy Widodo
Keyword(s):  
Data Collection ◽  
Price Index ◽  
Consumer Price Index ◽  
Original Data ◽  
Exponential Smoothing ◽  
Percentage Error ◽  
Monthly Data ◽  
Double Exponential ◽  
Double Exponential Smoothing ◽  
Exponential Smoothing Method

The Consumer Price Index (CPI) is an indicator that is often used to measure the inflation rate in an area, or can be interpreted as a comparison between the prices of a commodity package from a group of goods or services consumed by households over a certain period time. The spread of COVID-19 throughout the world affects the economy in Indonesia, especially Yogyakarta. Forecasting CPI data during the COVID-19 pandemic has the benefit of being an illustration of data collection in the CPI of D.I Yogyakarta Province in the predicted period. This is useful as a comparison with the original data at the time of data collection and publication, as well as a consideration in making policies and improving the economy. Researchers use the Double Exponential Smoothing (DES) method to predict the CPI of Yogyakarta D.I Province, which aims to determine the best forecasting model and forecasting results. This method is rarely used in research on CPI data forecasting in Yogyakarta. The data in this study are monthly data from March 2020 to August 2021. The highest CPI in Yogyakarta occurred in August 2021 at 107.21 or 107.2, while the lowest CPI in Yogyakarta occurred in April 2020 at 105.15 or 105.2. The average CPI in Yogyakarta per month is 106.1. The Mean Absolute Percentage Error (MAPE) value obtained from the DES method is 0.1308443%, so that the accuracy of the model is 99.869%. Forecasting with the DES method is quite well used in forecasting the CPI data of Yogyakarta in September 2020 - November 2021. The results of CPI forecasting in Yogyakarta using the DES method were 107.2602, 107.3104, and 107.3606 from September-November.

scholarly journals Comparison of Holt and Brown's Double Exponential Smoothing Methods in The Forecast of Moving Price for Mutual Funds

2020 ◽  
Vol 1 (2) ◽  
pp. 183-192
Author(s):  
Achmad Muchayan
Keyword(s):  
Mutual Funds ◽  
Exponential Smoothing ◽  
Percentage Error ◽  
Average Percentage ◽  
Smoothing Methods ◽  
Double Exponential ◽  
Brown's Method ◽  
Price Movements ◽  
Double Exponential Smoothing ◽  
Average Percentage Error

Mutual funds are one of the promising investment media where the risk is directly proportional to the size of investment growth. With proper forecasting of NAV price movements will greatly help investors to make purchases and sales transactions, therefore the authors offer the use of two different forecasting methods namely Brown's method and Holt method in double exponential smoothing to get predictions of NAV price movements. The effectiveness of the use of the method will be measured from the value of Mean Average Percentage Error (MAPE). From the calculation results obtained by the data that the Holt method produces forecasting for 1809,657 with the best α value of 0.6 and MAPE of 0.644373568, while for the Holt method obtained forecasting value of 1810,924 with the α value and the best β value of 0.9 and 0.1 and the smaller MAPE value of 0.61604262 . Looking at the amount of MAPE generated, the Holt method has a smaller forecasting error rate when compared to Brown’s method.

scholarly journals FORECASTING PRODUKSI PERIKANAN LAUT YANG DIJUAL DI TPI (TON) DENGAN METODE SINGLE EXPONENTIAL SMOOTHING

2020 ◽  
Vol 18 (2) ◽  
pp. 206
Author(s):  
Ivana Larasati Putri Navalina ◽  
Nur Indah Riwajanti ◽  
Sugeng Sulistyono ◽  
Ludfi Djajanto
Keyword(s):  
Marine Fish ◽  
Quantitative Research ◽  
National Level ◽  
Exponential Smoothing ◽  
Regional Level ◽  
Fish Production ◽  
The Government ◽  
Exponential Smoothing Method ◽  
Sea Fish ◽  
Single Exponential

The purpose of this study was to determine the results of forecasting the production of fish sold at TPI in 2018-2020. This is expected to help the government in the formulation of plans and strategies related to the production of marine fish to increase the GRDP of fisheries in Java (regional level) and fisheries GDP in Indonesia (national level) and to contribute in the field of information and macroeconomics. This research used descriptive quantitative research and used data obtained through the official website of the Central Statistics Agency. This study used the Single Exponential Smoothing method. The results of this study have shown that the areas with the lowest sea fish production are in the DI Yogyakarta area, so the government must devise a strategy to maximize fish production in order to increase the PRDB contribution in Yogyakarta.

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