scholarly journals USING EXPONENTIAL SMOOTHING METHOD IN FORECASTING DOMESTIC CREDIT TO PRIVATE SECTOR OF GHANA

2019 ◽  
Vol 10 (3) ◽  
Author(s):  
William Obeng-Amponsah ◽  
Sun Zehou ◽  
Elias Augustine Dey
Keyword(s):  
Private Sector ◽  
Exponential Smoothing ◽  
Smoothing Method ◽  
Annual Data ◽  
Best Interest ◽  
Policy Makers ◽  
Domestic Credit ◽  
The Government ◽  
Local Credit Market ◽  
Exponential Smoothing Method

The private sector of Ghana faces many problems with respect to raising capital for their operations; this is largely due to government relying heavily on the local credit market for funds for developmental projects. This study uses exponential smoothing method (ESM) in EViews to build a single sample model to forecast future domestic credit to private sector (DCPS) values in Ghana. Secondary annual data on DCPS spanning the period from 1982 to 2016 is used. The findings show that an exponential smoothing model with multiplicative error, additive trend and no seasonality fits the data best. The model had very small residual measures, which demonstrates a good model for forecasting. The estimated model is used to forecast the DCPS values for Ghana from the year 2017 to 2020. The results of this study will help private business people plan for the future. The results will also help policy makers to make informed decisions and formulate policies to improve the DCPS figures, since the private sector is the engine of growth, and crowding out would not be in the best interest of the government and the nation as a whole.

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 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 PERAMALAN KEDATANGAN WISATAWAN MANCANEGARA INDONESIA: METODE HOLT’S WINTER EXPONENTIAL SMOOTHING

2020 ◽  
Vol 18 (2) ◽  
pp. 233
Author(s):  
Fajar Islamiyah Rahmawati ◽  
Nurafni Eltivia ◽  
Kartika Dewi Sri Susilowati
Keyword(s):  
Decision Making ◽  
Exponential Smoothing ◽  
Tourism Industry ◽  
Smoothing Method ◽  
Seasonal Patterns ◽  
Microsoft Excel ◽  
Foreign Tourist ◽  
The Government ◽  
Quantitative Descriptive ◽  
Exponential Smoothing Method

This reseacrh aims to predict the arrival of foreign tourists in Indonesia using the Exponential Smoothing method. This research is quantitative descriptive. The data used are data of foreign tourist arrivals according to nationality taken from the Badan Pusat Statistik. Data is managed through the Microsoft Excel application. In determining RMSE, Solver Parameter help is used in Microsoft Excel to determine the lowest error rate. The data used in this research indicate that there are trend and seasonal patterns, so the most suitable Exponential Smoothing method is the Holt's Winter Exponential Smoothing method. The results of this research indicate that foreign tourist arrivals in Indonesia are predicted to increase in 2020. The results of this research are expected to help the government and related agencies in planning and decision making in the tourism industry.

scholarly journals MODELING AND FORECASTING OF INDIA’S DEFENSE EXPENDITURES USING BOX-JENKINS ARIMA MODEL

2021 ◽  
Vol 9 (2) ◽  
pp. 334-344
Author(s):  
Sapana Sharma ◽  
Sanju Karol
Keyword(s):  
Arima Model ◽  
Annual Data ◽  
Policy Makers ◽  
Rational Decision Making ◽  
Defense Expenditure ◽  
Forecasting Method ◽  
Modeling And Forecasting ◽  
One Step ◽  
The Government ◽  
The One

Many developed and developing countries are at the core of the security and peace agenda concerning rising defense expenditure and its enduring sustainability. The unremitting upsurge in defense expenditure pressurizes the government to rationally manage the resources so as to provide security and peace services in the most efficient, effective and equitable way. It is necessary to forecast the defense expenditure in India which leads the policy makers to execute reforms in order to detract burdens on these resources, as well as introduce appropriate plan strategies on the basis of rational decision making for the issues that may arise. The purpose of this study is to investigate the appropriate type of model based on the Box–Jenkins methodology to forecast defense expenditure in India. The present study applies the one-step ahead forecasting method for annual data over the period 1961 to 2020. The results show that ARIMA (1,1,1) model with static forecasting being the most appropriate to forecast the India’s defense expenditure.

scholarly journals TRIPLE EXPONENTIAL SMOOTHING: FORECASTING PERBANDINGAN PENUMPANG KERETA API DAN PESAWAT TERBANG

2020 ◽  
Vol 18 (2) ◽  
pp. 277
Author(s):  
Khoirin Azaro ◽  
Nur Indah Riwajanti ◽  
Anik Kusmintarti
Keyword(s):  
Consumer Demand ◽  
Exponential Smoothing ◽  
Smoothing Method ◽  
Seasonal Patterns ◽  
Efficient Planning ◽  
Exponential Method ◽  
Exponential Smoothing Method ◽  
Airline Company

This research aims to predict the number of train and airplane passengers in 2020. Forecasting of train and airplane passengers is interest to analyze and estimate consumer demand to help the train or airline company prepare effective and efficient planning. This type of research is descriptive quantitative and uses data taken from the Indonesian Statistic Agency (BPS). Data were analyzed using Exponential smoothing Method. Train and airplane passenger data shows trend and seasonal patterns so that the exponential method used is Triple Exponential smoothing. The results of the study show that train passengers in 2020 are increase. While forecast results related to aircraft passengers in 2020 also tend to increase.

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