scholarly journals Forecasting of Groundwater Tax Revenue Using Single Exponential Smoothing Method

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.

scholarly journals Single Exponential Smoothing Method to Predict Sales Multiple Products

INSIST ◽  
2018 ◽  
Vol 3 (2) ◽  
pp. 176
Author(s):  
Rendra Gustriansyah
Keyword(s):  
Prediction Error ◽  
Measurement Accuracy ◽  
Exponential Smoothing ◽  
Smoothing Method ◽  
Percentage Error ◽  
Standard Measurement ◽  
Multiple Products ◽  
Accuracy Of Prediction ◽  
Exponential Smoothing Method ◽  
Single Exponential

—Activity to predict sales multiple products intended for control of the number of existing stock, so the lack or excess stock can be minimized. When the number of sales can be accurately predicted, then the fulfilment of consumer demand can be cultivated in a timely and cooperation with suppliers maintained properly so that company can avoid losing sales and customers. This study aims to predict sales multiple products (6,877 products) using Single Exponential Smoothing (SES) approach, which is expected to improve the efficiency of the inventory system. Measurement accuracy of prediction in this study using a standard measurement Mean Absolute Percentage Error (MAPE), which is the most important criteria in analyzing the accuracy of the prediction. The results showed that the average of percentage prediction error of products using SES is high, because MAPE value obtained is 1.056% with a smoothing parameter α = 0.9

scholarly journals APPLICATION OF THE HOLT-WINTERS EXPONENTIAL SMOOTHING METHOD ON THE AIR POLLUTION STANDARD INDEX IN SURABAYA

2021 ◽  
Vol 10 (1) ◽  
pp. 53
Author(s):  
Silmi Muna ◽  
Kuntoro Kuntoro
Keyword(s):  
Air Pollution ◽  
Secondary Data ◽  
Exponential Smoothing ◽  
Smoothing Method ◽  
City Environment ◽  
The People ◽  
The Government ◽  
Environment Agency ◽  
Policies And Programs ◽  
Exponential Smoothing Method

The Air Pollution Standards Index (APSI) is an indicator that shows how clean or polluted the air is in a city. It also portrays the health impacts towards the people who breathe it in. Based on the Indonesian Ministry of Environment monitoring through the Air Quality Monitoring Station (AQMS), the city of Surabaya only had 22 up to 62 days of air categorized as good in a year. The purpose of this study was to forecast APSI as a scientific-based reference for making decisions and policies that were appropriate in tackling the effects of air pollution on health. This study was non-obstructive or non-reactive research. The research method used was time series to identify the time relationship. The data used were secondary data taken from the APSI documents from 2014 to 2019 at the Surabaya City Environment Agency. The results of this study obtained the best model through α (0.8), γ (0.5), and δ (0.6) with the values of MAPE (0.104355), MAD (0.00842), and MSD (0.001050) calculated with the Holt-Winters exponential smoothing method. The highest produced forecast value of APSI was in September 2020, and the smallest was in January 2020. This study suggests the government of Surabaya to create policies and programs to suppress the number within APSI.

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

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.

PARAMETER OPTIMIZATION OF SINGLE EXPONENTIAL SMOOTHING USING GOLDEN SECTION METHOD FOR GROCERIES FORECASTING

2019 ◽  
Vol 4 (2) ◽  
Author(s):  
Vivi Aida Fitria
Keyword(s):  
Golden Section ◽  
Exponential Smoothing ◽  
Food Prices ◽  
Percentage Error ◽  
Boundary Area ◽  
Section Method ◽  
Golden Section Method ◽  
Long Time ◽  
Exponential Smoothing Method ◽  
Single Exponential

Department of Agriculture and Food Security Malang City, especially in the Field of Food Supply Availability and Distribution requires a reference forecasting of food prices in Malang. The method used in the forecasting calculation is Single Exponential Smoothing. In the process of calculating the Single Exponential Smoothing method, it takes alpha parameters between 0 and 1. The problem is when to estimate the alpha value between 0 to 1 with trial error with the aim of producing minimal forecasting results. Therefore, this study aims to determine the optimal alpha value. The method used in this research is the Golden Section Method. The principle of Golden Section method in this study is to reduce the boundary area so as to produce a minimum MAPE (Mean Absolute Percentage Error) value The data used in this study is the price of 9 commodities of Groceries in Malang since January 1, 2016 until December 31, 2017. The results showed that the Golden Section method found that the optimal alpha value was 0.999 with MAPE average of 9 commodities is 0.79%. So with this golden section method researchers do not need a long time to determine alpha by trial error

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 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.

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