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 IMPLEMENTASI METODE EXPONENTIAL SMOOTHING UNTUK PERAMALAN KEDATANGAN WISATAWAN MANCANEGARA PADA PULAU BALI

2020 ◽  
Vol 18 (2) ◽  
pp. 171
Author(s):  
Nafis Sulthan ◽  
Nurafni Eltivia ◽  
Nur Indah Riwajanti
Keyword(s):  
Decision Making ◽  
Error Rate ◽  
Exponential Smoothing ◽  
Smoothing Method ◽  
Seasonal Patterns ◽  
Microsoft Excel ◽  
Foreign Tourist ◽  
Tourism Sector ◽  
Quantitative Descriptive ◽  
Exponential Smoothing Method

The purpose of this study is to predict the arrival of foreign tourists on the island of Bali by using the Exponential Smoothing method. This research is a quantitative descriptive. The data used in the study are data on foreign tourist arrivals from the air and sea routes taken from the Central Statistics Agency. Data is managed through the Microsoft Excel application. In determining the RMSE, the Solver Parameters help listed in Microsoft Excel is used to determine the lowest error rate. The data used in this study indicate that there are trend and seasonal patterns so that the most suitable Exponential Smoothing method is the Triple Exponential Smoothing method. The results of this study indicate that foreign tourist arrivals on the island of Bali are predicted to increase in 2020 although not too significant. The results of this study are expected to help the Bali Island government and related agencies in terms of planning and decision making to overcome the crisis on the island of Bali caused by the tourism sector.

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.

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 Penerapan Metode Pemulusan Eksponensial Ganda dan Tripel Untuk Meramalkan Kunjungan Wisatawan Mancanegara ke Indonesia

2018 ◽  
Vol 1 (1) ◽  
pp. 32-41
Author(s):  
Aditya Pranata ◽  
Muhajir Akbar Hsb ◽  
Teuku Akhdansyah ◽  
Samsul Anwar
Keyword(s):  
Exponential Smoothing ◽  
Smoothing Method ◽  
Central Bureau ◽  
Foreign Tourist ◽  
Double Exponential ◽  
Double Exponential Smoothing ◽  
Exponential Smoothing Method

ABSTRAK. Penelitian ini bertujuan untuk memprediksi jumlah kunjungan wisatawan asing ke Indonesia pada tahun 2018 dengan menggunakan metode Double Exponential Smoothing dan Triple Exponential Smoothing. Data yang digunakan adalah jumlah kunjungan wisatawan asing ke Indonesia sejak Januari 2008 hingga Desember 2017 yang diperoleh dari Badan Pusat Statistik (BPS) Indonesia. Hasil peramalan dengan menggunakan metode Double Exponential Smoothing menunjukkan bahwa jumlah kunjungan wisatawan asing pada tahun 2018 akan meningkat sebesar 5,49%. Sedangkan berdasarkan metode Triple Exponential Smoothing, diperkirakan jumlah kunjungan wisatawan asing akan meningkat sebesar 6,89%. Dengan demikian, dapat disimpulkan bahwa akan ada peningkatan yang signifikan dalam jumlah kunjungan wisatawan asing ke Indonesia pada tahun 2018. ABSTRACT. This study aims to predict the number of foreign tourist visiting to Indonesia in 2018 using Double Exponential Smoothing and Triple Exponential Smoothing. The data used is the number of foreign tourist visiting to Indonesia since January 2008 to December 2017 that obtained from the Indonesian Central Bureau of Statistics (BPS). The forecasting result using Double Exponential Smoothing method shows that the number of foreign tourist visiting in 2018 will increase by 5.49%. While based on Triple Exponential Smoothing method, it is estimated that the number of foreign tourists visiting will increase by 6.89%. Thus, it can be concluded that there will be a significant increase in the number of foreign tourist visiting to Indonesia in 2018.

scholarly journals ANALISIS FORECASTING DEMAND DENGAN METODE LINEAR EXPONENTIAL SMOOTHING (STUDI PADA: PRODUK BATIK FENDY, KLATEN)

2020 ◽  
Vol 16 (2) ◽  
pp. 81-89
Author(s):  
Nita Kusuma Wardani ◽  
Muhammad Roestam Afandi ◽  
Lilia Pasca Riani
Keyword(s):  
Secondary Data ◽  
Descriptive Study ◽  
Exponential Smoothing ◽  
Smoothing Method ◽  
Production Data ◽  
Sales Data ◽  
Forecasting Methods ◽  
Forecasting Method ◽  
Quantitative Descriptive ◽  
Exponential Smoothing Method

Abstrak: Tujuan dari penelitian ini adalah untuk mengevaluasi tingkat akurasi peramalan permintaan Batik Fendy menggunakan teknik MAPE. Adapun jenis penelitian ini merupakan penelitian deskriptif kuantitatif, menggunakan data sekunder dari penjualan perusahaan Batik Fendy periode bulan November 2018 - Onkoter 2019. Terdapat 5 tahapan dalam analisis data, yaitu 1) mentabulasikan data penjualan dan data produksi batik Fendy, 2) mengevaluasi metode peramalan penjualan yang dilakukan oleh perusahaan Batik Fendy dengan teknik MAPE, 3) memproyeksikan nilai alpha dan beta sebagai dasar peramalan linear exponential smoothing, 4) melakukan peramalan permintaan Batik Fendy dengan metode Linear Exponential Smoothing, dan 5) melakukan evaluasi metode peramalan dengan teknik MAPE. Hasil penelitian ini adalah nilai MAPE dari peramalan permintaan yang dilakukan oeh perusahaan Batik Fendy adalah sebesar 17,5%; angka ini menunjukkan tingkat persentase kesalahan paling tinggi pada varian Batik Sarimbit Lengan Panjang, kemudian dengan data penjualan varian ini dilakukan peramalan penjualan dengan metode Linear Exponential Smoothing dan diperoleh MAPE sebesar 9,21%. Sehingga dapat disimpulkan bahwa penggunaan metode Linear Exponential Smoothing dalam memprediksi penjualan Batik Fendy varian Sarimbit Lengan Panjang lebih akurat.Abstract: The purpose of this study was to evaluate the accuracy of forecasting demand for Batik Fendy using MAPE techniques. The type of this research is a quantitative descriptive study, using secondary data from the sales of the company Batik Fendy in the period November 2018 - October 2019. There are five stages in data analysis, namely 1) tabulating sales data and production data of Fendy batik, 2) evaluating sales forecasting methods conducted by the Batik Fendy company with the MAPE technique, 3) projecting alpha and beta values as the basis for forecasting linear, exponential smoothing, 4) forecasting requests for Batik Fendy with the Linear Exponential Smoothing method, and 5) evaluating the forecasting method with the MAPE technique. The results of this study are the MAPE value of demand forecasts made by the Batik Fendy company is 17.5%. This figure shows the highest percentage of error in the variant of the Sarimbit Long Sleeve Batik. With the sales data, this variant is forecasted by using the Linear Exponential Smoothing method and obtained a MAPE of 9.21%. So it can be concluded that the use of the Linear Exponential Smoothing method in predicting sales of the Sarimbit Arm Long Variant Batik is accurate.

scholarly journals The Analysis of Forecasting Demand Method of Linear Exponential Smoothing

2020 ◽  
pp. 7-18
Author(s):  
Nita Kusuma ◽  
Muhammad Roestam ◽  
Lilia Pasca
Keyword(s):  
Secondary Data ◽  
Descriptive Study ◽  
Exponential Smoothing ◽  
Smoothing Method ◽  
Production Data ◽  
Sales Data ◽  
Forecasting Methods ◽  
Forecasting Method ◽  
Quantitative Descriptive ◽  
Exponential Smoothing Method

The purpose of this study was to evaluate the accuracy of forecasting demand for Batik Fendy using MAPE techniques. The type of this research is a quantitative descriptive study, using secondary data from the sales of the company Batik Fendy in the period November 2018 - Onkoter 2019. There are 5 stages in data analysis, namely 1) tabulating sales data and production data of Fendy batik, 2) evaluating sales forecasting methods conducted by the Batik Fendy company with the MAPE technique, 3) projecting alpha and beta values ​​as the basis for forecasting linear exponential smoothing , 4) forecasting requests for Batik Fendy with the Linear Exponential Smoothing method , and 5) evaluating the forecasting method with the MAPE technique. The results of this study are the MAPE value of demand forecasts made by the Batik Fendy company is 17.5%; This figure shows the highest percentage of error in the variant of the Sarimbit Long Sleeve Batik, then with the sales data this variant is forecasted by using the Linear Exponential Smoothing method and obtained a MAPE of 9.21%. So it can be concluded that the use of the Linear Exponential Smoothing method in predicting sales of the Sarimbit Arm Long variant Batik is more accurate.

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.

Requirement Forecasting of Equipment’s Maintenance Spares-Parts Based on Exponential Smoothing Method

2012 ◽  
Vol 605-607 ◽  
pp. 9-13
Author(s):  
Xiao Chun Liu ◽  
Yong Liang Zhang ◽  
Ai Jun Huang ◽  
Li Ya Xu
Keyword(s):  
Exponential Smoothing ◽  
Smoothing Method ◽  
Forecasting Model ◽  
Microsoft Excel ◽  
Alternative Approach ◽  
Forecasting Method ◽  
Exponential Smoothing Method

Management of equipment’s maintenance spares-parts is one of important contents of equipment support. In allusion to the problem of requirement forecasting of maintenance equipment spares-parts, and based on exponential smoothing method, a requirement forecasting model of equipment’s maintenance spares-parts was built. Microsoft EXCEL was employed to forecast the equipment’s maintenance spares-parts requirements. The forecasting method provides a scientific and alternative approach to forecast requirement of equipment’s maintenance equipment.

Research on Package Materials with Properties of Packaging Materials for the Tianjin Port Throughput Prediction and Analysis

2014 ◽  
Vol 908 ◽  
pp. 107-110
Author(s):  
Min Zhang ◽  
Rui Pan
Keyword(s):  
Decision Making ◽  
Deep Understanding ◽  
Exponential Smoothing ◽  
Smoothing Method ◽  
Packaging Materials ◽  
Port Selection ◽  
Port Throughput ◽  
Exponential Smoothing Method ◽  
Package Materials ◽  
Selection Of

Through the understanding of the concept of the prediction and find the port to port the importance of decision-making as a whole, and then select the use of exponential smoothing method to forecast the port throughput, on the property of the transport of goods packaging materials on the basis of deep understanding, goods to the port selection of packaging materials has a strong guiding significance.

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