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Journal articles on the topic 'Exponential forecasting method'

Author: Grafiati

Published: 3 June 2025

Last updated: 19 July 2025

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1

Devira, Annisa Suci, Yuki Novia Nasution, and Suyitno Suyitno. "Peramalan Pendapatan Asli Daerah Kota Samarinda Menggunakan Metode Double Exponential Smoothing Dari Brown." EKSPONENSIAL 14, no. 1 (2023): 41. http://dx.doi.org/10.30872/eksponensial.v14i2.1138.

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Forecasting is a technique for estimating a value in the future by paying attention to past data and current data. One of the forecasting methods for exponentially increasing or decreasing data patterns is Exponential Smoothing. Exponential Smoothing is a method that shows the weighting decreases exponentially with respect to the older observation values. The linear model of the Exponential Smoothing method that uses a two-time smoothing process is Brown's Double Exponential Smoothing method. This study aims to get a forecast of Regional Original Income (PAD) in Samarinda with the double expon

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Mironov, A. N., S. U. Pirogov, A. I. Petuhov, V. K. Sinilov, and O. L. Shestopalova. "Uneven time series forecasting using a modified exponential smoothing method." E3S Web of Conferences 531 (2024): 03020. http://dx.doi.org/10.1051/e3sconf/202453103020.

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The article is devoted to the problem of forecasting time series with an uneven distribution of observations over time. The exponential smoothing model is used as the basic forecasting model, in which the variable weights of observations decrease exponentially. The exponential smoothing model allows us to take into account the attenuation of the correlation of cross sections of a random process of time series change over time. However, this does not take into account the factors of temporal unevenness of the results of observations and the finiteness of the sample of observations. The article

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Deakshinamurthyt. "DEMAND FORECASTING FOR CEMENT IN INDIA 2030." International Journal of Marketing & Financial Management Volume 5, Issue 8, Aug-2017 (2017): pp 09–13. https://doi.org/10.5281/zenodo.888259.

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The paper estimates the demand forecasting for cement in India for 2030 based on exponential demand forecasting, linear forecasting and polynomial method. Cement being an important raw material for construction and infrastructure developments it supports in constructing a better nation. Three different methods for forecasting of cement production is done. The exponential method is suitable for high economic activity in India and polynomial (degree two) for average level of economic activity and linear forecasting for a low level of economic activity in the country.

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Hayuningtyas, Ratih Yulia. "Sistem Informasi Peramalan Persediaan Barang Menggunakan Metode SES Dan DES." Indonesian Journal on Software Engineering (IJSE) 4, no. 1 (2019): 1–6. http://dx.doi.org/10.31294/ijse.v4i1.6228.

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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

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Hasan, M. Babul, and Md Nayan Dhali. "Determination of Optimal Smoothing Constants for Exponential Smoothing Method & Holt’s Method." Dhaka University Journal of Science 65, no. 1 (2017): 55–59. http://dx.doi.org/10.3329/dujs.v65i1.54509.

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This paper concentrates on choosing the appropriate smoothing constants for Exponential Smoothing method and Holt’s method. These two methods are very important quantitative techniques in forecasting. The accuracy of forecasting of these techniques depends on Exponential smoothing constants. So, choosing an appropriate value of Exponential smoothing constants is very crucial to minimize the error in forecasting. In this paper, we have showed how to choose optimal smoothing constants of these techniques for a particular problem. We have demonstrated the techniques by presenting a real life exam

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Wofuru-Nyenke, Ovundah. "Predicting demand in a bottled water supply chain using classical time series forecasting models." Journal of Future Sustainability 2, no. 2 (2022): 65–80. http://dx.doi.org/10.5267/j.jfs.2022.9.006.

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In this paper, various classical time series forecasting methods were compared to determine the forecasting method with the highest accuracy in predicting demand of the 50cl product of a bottled water supply chain. The classical time series forecasting methods compared are the moving average, weighted moving average, exponential smoothing, adjusted exponential smoothing, linear trend line, Holt’s model, and Winter’s model. These methods were evaluated to determine the method with the least Mean Absolute Deviation (MAD) value and hence the highest forecasting accuracy. From the results, the wei

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Bas, Eren, Erol Egrioglu, and Ufuk Yolcu. "Bootstrapped Holt Method with Autoregressive Coefficients Based on Harmony Search Algorithm." Forecasting 3, no. 4 (2021): 839–49. http://dx.doi.org/10.3390/forecast3040050.

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Exponential smoothing methods are one of the classical time series forecasting methods. It is well known that exponential smoothing methods are powerful forecasting methods. In these methods, exponential smoothing parameters are fixed on time, and they should be estimated with efficient optimization algorithms. According to the time series component, a suitable exponential smoothing method should be preferred. The Holt method can produce successful forecasting results for time series that have a trend. In this study, the Holt method is modified by using time-varying smoothing parameters instea

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Mentari, Maharani Sari Mutiara, and Irwan Iftadi. "Selection of the Best Forecasting Method at PT. Indaco Warna Dunia." Teknoin 28, no. 01 (2023): 1–10. http://dx.doi.org/10.20885/teknoin.vol28.iss1.art1.

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PT. Indaco Warna Dunia is a decorative paint company in Indonesia that produces products under the brands Envi, Belazo, and Top Seal. Preliminary observations revealed that the forecasting method used by the company is ineffective and inaccurate. This inaccurate forecast result company’s problem in fulfilling the demand. This study aims to select the best forecasting method to improve forecast effectiveness and accuracy. The research was conducted at the Tarakan depot, and the products understudy were a fast-moving product category, specifically the Envi brand. Several forecasting methods such

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Andreyanto, Muhammad Faisal, and Hana Catur Wahyuni. "Comparison of Forecasting Techniques Moving Average and Double Exponential Smoothing in Sugar Production for Enhanced Maintenance Preparedness Ahead of Milling Season." Procedia of Engineering and Life Science 7 (March 18, 2024): 620–27. http://dx.doi.org/10.21070/pels.v7i0.1558.

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Sugar as a commodity has a very vital role, not only being a basic need for Indonesian society, but also an inseparable element in various industrial sectors. The aim of this research is to compare sugar production forecasting systems by comparing two methods using moving averages and double exponential smoothing (holt's method). Forecasting is the process of projecting or predicting future events with a structured planning approach. Forecasting in sugar production is needed to find out whether the next month can meet the target or not. The amount of sugar production is used as a reference for

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Kılıç Topuz, Bakiye, Mehmet BOZOĞLU, NEVRA ALHAS EROĞLU, and Uğur BAŞER. "Forecasting of Onion Sown Area and Production in Turkey Using Exponential Smoothing Method." Turkish Journal of Forecasting 03, no. 2 (2019): 39–46. http://dx.doi.org/10.34110/forecasting.660377.

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D’Sa, Mel M., Robert S. Nakagawa, David S. Hill, and Joseph K. Tan. "Exponential smoothing method for forecasting drug expenditures." American Journal of Health-System Pharmacy 51, no. 20 (1994): 2581–88. http://dx.doi.org/10.1093/ajhp/51.20.2581.

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Lim, P. Y., and C. V. Nayar. "Solar Irradiance and Load Demand Forecasting based on Single Exponential Smoothing Method." International Journal of Engineering and Technology 4, no. 4 (2012): 451–55. http://dx.doi.org/10.7763/ijet.2012.v4.408.

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Habsari, Humairo Dyah Puji, Ika Purnamasari, and Desi Yuniarti. "FORECASTING USES DOUBLE EXPONENTIAL SMOOTHING METHOD AND FORECASTING VERIFICATION USES TRACKING SIGNAL CONTROL CHART (CASE STUDY: IHK DATA OF EAST KALIMANTAN PROVINCE)." BAREKENG: Jurnal Ilmu Matematika dan Terapan 14, no. 1 (2020): 013–22. http://dx.doi.org/10.30598/barekengvol14iss1pp013-022.

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Abstrak Peramalan merupakan suatu teknik untuk memperkirakan suatu nilai pada masa yang akan datang dengan memperhatikan data masa lalu maupun data saat ini. Data yang menunjukan suatu trend, cocok dengan metode peramalan double exponential smoothing dari Brown atau metode double exponential smoothing dari Holt. Peramalan metode double exponential smoothing pada penelitian ini diaplikasikan pada data IHK Provinsi Kalimantan Timur periode Bulan Januari Tahun 2016 hingga Bulan Februari Tahun 2019 yang berpola trend. Tujuan dari penelitian ini adalah memperoleh hasil perbandingan akurasi me

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Wofuru-Nyenke, Ovundah King. "Forecasting Model Accuracy Assessment in a Bottled Water Supply Chain." International Journal of Engineering and Modern Technology 8, no. 5 (2023): 101–8. http://dx.doi.org/10.56201/ijemt.v8.no5.2022.pg101.108.

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This study presents an accuracy assessment of various classical time series forecasting methods to determine the most accurate forecasting method for predicting demand of the 50cl product of a bottled water supply chain. The classical time series forecasting methods compared are the moving average, weighted moving average, exponential smoothing, adjusted exponential smoothing, linear trend line, Holt’s model, and Winter’s model. The Mean Absolute Percent Deviation (MAPD) value was determined for the various forecasting methods to find the forecasting method with the least MAPD and hence the hi

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Hirzi, Ristu Haiban, Umam Hidayaturrohman, Kertanah Kertanah, M. Hadiyan Amaly, and Rody Satriawan. "Prediksi Jumlah Wisatawan Menggunakan Metode Random Forest, Single Exponential Smoothing dan Double Exponential Smoothing di Provinsi NTB." Jambura Journal of Probability and Statistics 4, no. 1 (2023): 47–55. http://dx.doi.org/10.34312/jjps.v4i1.17088.

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The aim of study is to forecast global tourist visits and compare the forecasting methods to determine the best method using random forest, single exponential smoothing and double exponential smoothing, respectively. These methods are applied in global tourist visit data in West Nusa Tenggara Province. Random forest, single exponential smoothing and double exponential smoothing are familiar methods and are frequently utilized in forecasting. In addition, the three methods have great accuracy for time series data, such as data of global tourist visits. The data used in this study is data of glo

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Anshori, Muhammad Hizam, and Atikha Sidhi Cahyana. "Forecasting Analysis of Raw Material Demand in the Battery Breaker Production Process at PT IMLI." Procedia of Engineering and Life Science 7 (February 21, 2024): 1–7. http://dx.doi.org/10.21070/pels.v7i0.1588.

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Accurate demand forecasting is crucial for companies engaged in smelting, such as PT IMLI, to prevent shortages and inventory increases. This research aims to determine the most appropriate forecasting method for raw material demand based on historical data. Three methods were used: moving average with n = 3 and n = 5, and exponential smoothing with α = 0.2. The results showed that the Exponential Smoothing Method with α = 0.2 had the smallest error rate, with a MAPE value of 23%, MAD of 411, and MSE of 293303. This method can be used to optimize demand forecasting for the next period, ensurin

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Michael, ., and Adhi Utama Akbar. "Sales and Operation Analysis: A Case Study in Pt. Berkat Popok Bahagia." International Journal of Current Science Research and Review 07, no. 01 (2024): 410–23. https://doi.org/10.5281/zenodo.10527052.

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Abstract : The purpose of this paper is to help solve one of the current existing issues of PT. Berkat Popok Bahagia which is SKUs being out of stock. It turns out that there are several reasons for this. The first reason is the amount of the stock of each SKU in the system differs from the amount of stock in the warehouse. The second reason is the demand from the distributors is not in sync with the sales and operational planning team, making it when the distributors order products (SKU) from the factory, the product is not available because it might not be in the production process. The thir

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Fauziah, Fauziah, Yulia Istia Ningsih, and Eva Setiarini. "Analisis Peramalan (Forecasting) Penjualan Jasa Pada Warnet Bulian City di Muara Bulian." Eksis: Jurnal Ilmiah Ekonomi dan Bisnis 10, no. 1 (2019): 61. http://dx.doi.org/10.33087/eksis.v10i1.160.

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In the business world Forecasting is one of the most important factors that must be applied in a business. Forecasting is a method for estimating a value in the future by using past data effectively and efficiently. This research was conducted at Warnet Bulian City In this study, the author discusses the analysis of forecasting (Forecasting) sales of services at the Bulian City internet cafe in Muara Bulian. Forecasting is done using three methods namely the MOVA (Moving Average) method, the WMA (Weight Moving Average) method and the Exponential Smoothing Method by comparing the smallest error

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Wijaya, Rahmat Adi, Rr. Erlina, and Nova Mardiana. "Comparison of Moving Average and Exponential Smoothing Methods in Sales Forecasting of Banana Chips Products in Pd. Dwi Putra Tulang Bawang Barat." Journal of Finance and Business Digital 2, no. 2 (2023): 193–208. http://dx.doi.org/10.55927/jfbd.v2i2.4913.

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Sales forecasts predict a company's sales. PD Dwi Putra's banana chip sales have fluctuated every month for the past few years, resulting in stock shortages and excesses. Forecasting using historical sales data uses time series methods like moving average and exponential smoothing. This study compares the two forecasting methods to find the lowest error rate and the best method for the company to use for the next four years. The exponential smoothing method outperforms the moving average method for MAPE, MSE, and MAD values, so it is used for future forecasting. According to research, companie

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Murpratiwi, Santi Ika, Dewa Ayu Indah Cahya Dewi, and Arik Aranta. "Accuracy Analysis of Predictive Value in Transaction Data of Service Company Using Combination of K-Means Clustering and Time Series Methods." Journal of Computer Science and Informatics Engineering (J-Cosine) 5, no. 1 (2021): 30–39. http://dx.doi.org/10.29303/jcosine.v5i1.378.

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Profit decline is a frightening problem for service companies. The solution to prevent this is by analyzing data transactions using data mining and forecasting. K-Means used to cluster the level of car damage based on the number of panels repaired and the duration of repaired. The results of K-Means used as material for analysis the best time-series method for transaction data. The methods analyzed include the moving average, single exponential smoothing, double exponential smoothing, and winter's method. Single exponential smoothing is the most suitable forecasting method with transaction dat

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Wijono, Joko, Ninny Siregar, and M. Banjarnahor. "Peramalan Tingkat Permintaan LPG PT. Pertamina (Persero) Di Elpiji Tandem." JOURNAL OF INDUSTRIAL AND MANUFACTURE ENGINEERING 2, no. 2 (2019): 35. http://dx.doi.org/10.31289/jime.v2i2.2434.

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<h1>LPG that produced by PT. Pertamina (Persero) unit Pengolahan I Pangkalan Brandan cames from natural gas. LPG usually used by people for industry and home needs. Most of high-end community prefer to consume to fuel oil, outfil legible job decay (durable) bat need big investment(because the storages of LPG or LPG bottle is expensive). Most of LPG consumption for north sumatera consumer supplied by PT. Pertamina (Persero) Unit Pengolahan I Pangkalan Berandan. For maintaining LPG continuity, so demand forecasting is a neccessary for the future. Considering the decline of LPG production,

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Wineka Nirmala, Virgin, Dikdik Harjadi, and Robi Awaluddin. "Sales Forecasting by Using Exponential Smoothing Method and Trend Method to Optimize Product Sales in PT. Zamrud Bumi Indonesia During the Covid-19 Pandemic." International Journal of Engineering, Science and Information Technology 1, no. 4 (2021): 59–64. http://dx.doi.org/10.52088/ijesty.v1i4.169.

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Forecasting is important for a company in achieving goals effectively and efficiently. Forecasting aims to determine the next steps to be taken based on historical data. PT. Zamrud Bumi Indonesia is one of the manufacturing companies in the management of agricultural liquid fertilizers with the trademark “Power Bumi”. The purpose of this study is to analyze the sales pattern of Power Bumi products during the covid-19 pandemic and compare the forecasting method that is able to produce the smallest error value in forecasting sales of Power Bumi products PT. Zamrud Bumi Indonesia. This study uses

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Albani, Nabila Tiara, and Wahyudin Wahyudin. "Peramalan Jumlah Kebutuhan Packaging Papper Photocopy (PPC) PT. Y Menggunakan Metode Moving Avarage dan Exponential Smoothing." Industrika : Jurnal Ilmiah Teknik Industri 8, no. 3 (2024): 488–94. http://dx.doi.org/10.37090/indstrk.v8i3.1222.

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In the era of globalization, industry and trade in Indonesia face fierce competition. Technological advances require quality human resources from formal and non-formal educational institutions with supporting facilities. This research focuses on solving safety stock problems using the Exponential Smoothing and Moving Average methods. Due to the current changing market demand, the results of data processing carried out using the Quality Management (QM) program for Windows show that the forecasting method with the Moving Average approach has the highest Mean Absolute Percentage Error (MAPE) valu

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Barman, Nandita, M. Babul Hasan, and Md Nayan Dhali. "Advising an Appropriate Forecasting Method for a Snacks Item (Biscuit) Manufacture Company in Bangladesh." Dhaka University Journal of Science 66, no. 1 (2018): 55–58. http://dx.doi.org/10.3329/dujs.v66i1.54545.

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In this paper, we study the most appropriate short-term forecasting methods for the newly launched biscuit factory produces different types of biscuits. One of them is nut-orange twisted biscuits. As it is a newly launched biscuit factory, it does not use any scientific method to find future demand of their products to produce for the purpose of sales. Having an error free production as well as a good inventory management we try to find an appropriate forecasting method for the sets of data we analyzed for that specific production. Several forecasting methods of time series forecasting such as

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Fredriksz, Grace. "PERAMALAN PERMINTAAN PRODUK TIRAI MENGGUNAKAN METODE MOVING AVERAGE DAN EXPONENTIAL SMOOTHING (Studi Kasus pada Meubel Sarira Waitatiri Maluku Tengah)." JRMA | Jurnal Riset Manajemen dan Akuntansi 10, no. 2 (2022): 107–22. http://dx.doi.org/10.33508/jrma.v10i2.1111.

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This study aims to determine the most effective method of demand forecasting for curtain products at the Sarira furniture company in Waitatiri, Central Maluku, so that the production of the goods is not too many. The demand forecasting method used in this research is the Moving Average method and the Exponential Smoothing method. The methods analyzed are the 3-month and 5-month Moving Average methods, as well as Exponential Smoothing with values of 0.1, 0.5, and 0.9. The results of each method are compared based on the level of error. The calculation of how far a prediction is made is called t

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Pinem, Kelvin Fernando, Bagus Mulyawan, and Novario Jaya Perdana. "IMPLEMENTATION OF MINIMUM STOCK DETERMINATION USING PREDICTION AND ECONOMIC ORDER QUANTITY (EOQ) METHOD." Jurnal Ilmu Komputer dan Sistem Informasi 9, no. 1 (2021): 148. http://dx.doi.org/10.24912/jiksi.v9i1.11586.

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In an effort to get competitive prices, one must be able to organize the planning of the availability of the goods it owns so that it can maintain a balance between demand and the existing stock of goods (supply). This application aims to create a precise forecasting system that is useful for determining the inventory of goods in stock that must be done in accordance with the old sales data that have occurred. The method used in this research is forecasting to predict or predict the inventory of goods, then calculating the Economic Order Quantity (EOQ) to return the number of items ordered whi

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Pamungkas, A., R. Puspasari, A. Nurfiarini, R. Zulkarnain, and W. Waryanto. "Comparison of Exponential Smoothing Methods for Forecasting Marine Fish Production in Pekalongan Waters, Central Java." IOP Conference Series: Earth and Environmental Science 934, no. 1 (2021): 012016. http://dx.doi.org/10.1088/1755-1315/934/1/012016.

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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 ex

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Rahayu, Sherly Indriani, and Jauhari Arifin. "Penerapan Metode Double Exponential Smoothing dan Regresi Linier pada Peramalan Persediaan Packaging di PT. XYZ." Industrika : Jurnal Ilmiah Teknik Industri 7, no. 3 (2023): 336–46. http://dx.doi.org/10.37090/indstrk.v7i3.1095.

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PT. XYZ is one of the company that produces packaging materials, one of which is sacks. This study aims to determine forecasting on sack raw material packaging using the Double Exponential Smoothing method and Linear Regression in these calculations using manual calculation methods using Microsoft excel. The two methods are then identified as having the smallest error value. The data used in this study uses secondary data in the form of sales reports of raw material packaging in the past. Based on the forecasting results obtained using the Double Exponential Smoothing and Linear Regression met

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Mi, Jianwei, Libin Fan, Xuechao Duan, and Yuanying Qiu. "Short-Term Power Load Forecasting Method Based on Improved Exponential Smoothing Grey Model." Mathematical Problems in Engineering 2018 (2018): 1–11. http://dx.doi.org/10.1155/2018/3894723.

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In order to improve the prediction accuracy, this paper proposes a short-term power load forecasting method based on the improved exponential smoothing grey model. It firstly determines the main factor affecting the power load using the grey correlation analysis. It then conducts power load forecasting using the improved multivariable grey model. The improved prediction model firstly carries out the smoothing processing of the original power load data using the first exponential smoothing method. Secondly, the grey prediction model with an optimized background value is established using the sm

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Seng, Hansun, and Subanar. "Brown's Weighted Exponential Moving Average Implementation in Forex Forecasting." TELKOMNIKA Telecommunication, Computing, Electronics and Control 15, no. 3 (2017): 1425–32. https://doi.org/10.12928/TELKOMNIKA.v15i3.5410.

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In 2016, a time series forecasting technique which combined the weighting factor calculation formula found in weighted moving average with Brown’s double exponential smoothing procedures had been introduced. The technique is known as Brown’s weighted exponential moving average (B-WEMA), as a new variant of double exponential smoothing method which does the exponential filter processes twice. In this research, we will try to implement the new method to forecast some foreign exchange, or known as forex data, including EUR/USD, AUD/USD, GBP/USD, USD/JPY, and EUR/JPY data. The time ser

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Aini, Aini Nur, Rani Purbaningtyas, and R. Dimas Adityo. "Forecasting Sales 3 Kg Lpg Using Single Exponential Smoothing Method." JEECS (Journal of Electrical Engineering and Computer Sciences) 2, no. 2 (2017): 281–86. http://dx.doi.org/10.54732/jeecs.v2i2.153.

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Forecasting is a very important in corporate strategy planning. Single Exponential Smoothing Method is one of thetime series forecasting methods. The purpose of this study is the number of selling period can be subsequent profitscan be sold to customers with appropriate obtained CV. Damayanti every month. This research uses selling dataobtained by selling 3kg LPG for 7 years from january 2009 until December 2016. The result of this forecasting isdone by Single Exponential Smoothing method with the result of error calculation and selected forecasting resultwhich has minimum MAE. The alpha value

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Zahrunnisa, Afifah, Renanta Dzakiya Nafalana, Istina Alya Rosyada, and Edy Widodo. "PERBANDINGAN METODE EXPONENTIAL SMOOTHING DAN ARIMA PADA PERAMALAN GARIS KEMISKINAN PROVINSI JAWA TENGAH." Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika 2, no. 3 (2021): 300–314. http://dx.doi.org/10.46306/lb.v2i3.91.

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Forecasting is a technique that uses past data or historical data to determine something in the future. Forecasting methods with time series models consist of several methods, such as Double Exponential Smoothing (Holt method) and ARIMA. DES (Holt method) is a method that is used to predict time series data that has a trend pattern. ARIMA model combines AR and MA models with differencing order d. The poverty line is calculated by finding the total cost of all the essential resources that an average human adult consumes in one year. The lack of poverty reduction in an area is the lack of inform

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Gunarti, Triana Sri, Baibul Tujni, and Imam Solikin. "DETERMINE THE MATERIAL INVENTORY FORECASTING METHOD BASED ON THE SMALLEST ERROR." JURTEKSI (Jurnal Teknologi dan Sistem Informasi) 9, no. 4 (2023): 691–98. http://dx.doi.org/10.33330/jurteksi.v9i4.2650.

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Abstract: The research was conducted at TB Bina Karya which is engaged in the sale and purchase of building materials. This research was conducted to predict building materials for the next period. The forecasting methods used in this study are single moving average (SMA), weighted moving average (WMA), and single exponential smoothing (SES). This study also discusses the error calculation of the forecasting method, the forecasting method which produces the smallest error value is used for making decisions in purchasing materials. The purpose of this research is to speed up the decision making

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Candio, Syaifullah Adam, Arlene Henny Hiariey, and Ronald John Djami. "PERBANDINGAN METODE DOUBLE EXPONENTIAL SMOOTHING DAN TRIPLE EXPONENTIAL SMOOTHING DALAM MEMPREDIKSI TINGKAT KRIMINALITAS." PARAMETER: Jurnal Matematika, Statistika dan Terapannya 3, no. 01 (2024): 49–60. http://dx.doi.org/10.30598/parameterv3i01pp49-60.

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From 2010 to 2022, crime in Indonesia, especially Maluku Province, tends to increase compared to previous years. Considering these problems, a crime rate prediction system is needed so that the Maluku Provincial Police is able to estimate the quantity and type of crime that is likely to occur in the future. One of the prediction methods that has been used for crime prediction is Exponential Smoothing (ES). The Smoothing method is applied to obtain predictions based on time-series data. In this discussion, the author will compare the forecasting methods of Double Exponential Smoothing, and Trip

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Liu, Bin Xiang, Qun Cao, and Xiang Cheng. "Application of Self-Adaptive Exponential Smoothing Method in the Water Quality Forecast of Poyang Lake." Advanced Materials Research 518-523 (May 2012): 1464–67. http://dx.doi.org/10.4028/www.scientific.net/amr.518-523.1464.

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The smoothing parameter is a constant when forecasting water quality using exponential smoothing, which usually renders the error to be enlarged, but the assumption of constant is out of accord with the practice. Based on the deep analysis of deficiency of traditional exponential smoothing, this paper establishes self-adaptive exponential smoothing model and compares the forecast result. It is proved that the dynamic characteristic of water quality can be better reflected and the forecasting precision can be improved further by self-adaptive exponential smoothing model.

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Ramesh, M., M. Sunitha, and M. Venkataramanaiah. "Holt's exponential smoothing method for forecasting silver prices." South Asian Journal of Marketing & Management Research 6, no. 8 (2016): 1. http://dx.doi.org/10.5958/2249-877x.2016.00006.0.

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Ramesh, M., K. Radhaiah, and M. Venkataramanaiah. "Forecasting gold prices using holt's exponential smoothing method." ACADEMICIA: An International Multidisciplinary Research Journal 6, no. 7 (2016): 136. http://dx.doi.org/10.5958/2249-7137.2016.00032.x.

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Shastri, Sourabh, Amardeep Sharma, Vibhakar Mansotra, Anand Sharma, Arun Singh Bhadwal, and Monika Kumari. "A Study on Exponential Smoothing Method for Forecasting." International Journal of Computer Sciences and Engineering 6, no. 4 (2018): 482–85. http://dx.doi.org/10.26438/ijcse/v6i4.482485.

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Manalu, Abraham, Dewi Roito, Eika Rizkiadina, and Yonata Laia. "Analysis Forecasting Sales With Single Exponential Smoothing Method." Paradigma - Jurnal Komputer dan Informatika 24, no. 2 (2022): 135–38. http://dx.doi.org/10.31294/paradigma.v24i2.1255.

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Currently, as we know that the use of computer-based systems, almost everyone's activities depend on computer-based systems. one that is currently very adequate in the use of the application is the sales system, in this research the problem faced by the company is the difficulty of determining the amount of inventory stock each month. The reason is because the number of types of goods is not small so this is the cause of the lack of fulfillment of consumer demand every day. Companies that do have a number of inventories whose stock or inventory is on a large scale, so it needs a special system

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Haya, Miratul, and Dadang Sukandar. "Indonesian Grain Production Forecasting, Moving Average Method, and Exponential Smoothing." AGRITROPICA : Journal of Agricultural Sciences 6, no. 1 (2023): 14–21. http://dx.doi.org/10.31186/j.agritropica.6.1.14-21.

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National food security requires grain for food adequacy, which is then processed into rice as a cereal product, one of the most dominant food commodities for the majority of Indonesian people. The analysis of the ratio normative consumption per capita to cereal production shows that 39.66% of districts in Indonesia experience a deficit in food availability, partly due to population growth which an increase has not matched in cereal production. The purpose of this research is to perform forecasting on the amount of grain production as a reference in formulating a strategy for supplying grain to

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Nursyanti, Yevita. "MINIMASI BIAYA PRODUKSI PADA PRODUK WINKER RELAY MELALUI PERENCANAAN PRODUKSI AGREGAT." Jurnal Penelitan Ekonomi dan Bisnis 4, no. 2 (2019): 143–52. http://dx.doi.org/10.33633/jpeb.v4i2.2556.

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The purpose of this research is to determine demand forecasting on relay winker products and to determine the aggregate planning of relay winker products that produce minimum costs. The method used in this study is a comparative quantitative method. The data used in conducting aggregate planning are data from forecasting calculations with the chosen method, forecasting is calculated using several methods, namely the Moving Average, Exponential Smoothing, Double Exponential Smoothing, Quadratic and Linear Regression methods. Select this method by looking for the MAPE value. The method that has

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Aji, Briyan Gifari, Dwi Chandra Aditya Sondawa, Fairuz Aqila Anindika, and Dwi Januarita. "Analisis Peramalan Obat Menggunakan Metode Simple Moving Average, Weighted Moving Average, Dan Exponential Smoothing." JURIKOM (Jurnal Riset Komputer) 9, no. 4 (2022): 959. http://dx.doi.org/10.30865/jurikom.v9i4.4454.

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Forecasting is one of the essential measures in decision making, especially for estimating the number of needs. Some large companies often hire consultants to analyze and advise on forecast product demand. Especially in the health sector, forecasting is needed to meet customer drug demand. In the last two years, the Healthy Prayer Clinic experienced problems in planning the procurement of non-generic drugs due to the COVID-19 pandemic, where the number of drug requests was greater than the number of available drug stocks. This happened because the Healthy Prayer Clinic ordered non-generic drug

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Barman, Nandita, and M. Babul Hasan. "Comparison of Forecasting Techniques for Short-term and Long-term Real Life Problems." Dhaka University Journal of Science 65, no. 2 (2017): 139–44. http://dx.doi.org/10.3329/dujs.v65i2.54523.

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In this paper, we analyze the most appropriate short-term and long term forecasting methods for our practical life where several methods of time series forecasting are available such as the Moving Averages method, Linear Regression with Time, Exponential Smoothing, Holt‘s Method, Holt-Winter‘s Method etc. This paper mainly concentrates on the Holt- Winters Exponential Smoothing technique as applied to time series that exhibit seasonality. The accuracy of the out-of-sample forecast is measured using MSE, MAPE, MAD. We will observe that the empirical results from the study indicate that the Holt

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Ana Risqa JL and Tuti Maryani. "Cacao (Theobroma cacao) Production Forecasting in Lampung Province with the Double Exponential Smoothing Method." Formosa Journal of Multidisciplinary Research 2, no. 11 (2023): 1765–74. http://dx.doi.org/10.55927/fjmr.v2i11.6733.

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Cacao (Theobroma cacao) is one of the Indonesian plantation commodities which can be processed into cacao and chocolate products which contain natural antioxidants. In Lampung, the cacao commodity is very superior because every year it has significantly increased and cocoa production is one of the plantation commodities that has contributed to the export development of Lampung Province. In this case, forecasting can be used to estimate that cacao production will always experience an increase or decrease. Another function is to provide information for farmers and the government. Forecasting use

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Faisol, Faisol, and Sitti Aisah. "PENERAPAN METODE EXPONENTIAL SMOOTHING UNTUK PERAMALAN JUMLAH KLAIM DI BPJS KESEHATAN PAMEKASAN." Jurnal Matematika "MANTIK" 2, no. 1 (2016): 46. http://dx.doi.org/10.15642/mantik.2016.2.1.46-51.

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Time series model is the model used to predict the future using past data, one example of a time series model is exponential smoothing. Exponential smoothing method is a repair procedure performed continuously at forecasting the most recent data. In this study the exponential smoothing method is applied to predict the number of claims in the health BPJS Pamekasan using data from the period January 2014 to December 2015, the measures used to obtain the output of this research there are four stages, namely 1) the identification of data, 2) Modeling, 3) forecasting, 4) Evaluation of forecasting r

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Dwiputri, Inayati Nuraini, Muhammad Syam Kusufi, and Albertus Girik Allo. "Projections of Regional Macroeconomic Conditions using the Univariate Forecasting Method." Economics Development Analysis Journal 8, no. 3 (2020): 329–42. http://dx.doi.org/10.15294/edaj.v8i3.30188.

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The prediction of future macroeconomic conditions is needed by the government to carry out the planning and budgeting. This study predicts macro indicators in Hulu Sungai Utara Regency in the period 2017-2022. The method used is univariateforecasting, which includes the ARIMA model, exponential smoothing, and exponential smoothing with trend adjustment. The macroeconomic indicators used in this study are real Gross Domestic Regional Product (GDRP), economic growth, unemployment rate, and income distribution. The results of the analysis show that Brown's forecasting model is predicted that the

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Manuputty, A., R. Patiekon, M. Z. Waliulu, R. Siwalette, D. C. Latumahina, and M. Y. Matdoan. "Poverty Level Forecasting in Maluku Province Using the Exponential Smoothing Method." Formosa Journal of Computer and Information Science 1, no. 2 (2022): 117–32. http://dx.doi.org/10.55927/fjcis.v1i2.2005.

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The purpose of this study is to predict the poverty rate in Maluku Province in 2021-2025 using the Exponential Smoothing method. The Exponential Smoothing method is a moving average forecasting method that gives exponential or multilevel weight to the latest data so that the latest data will get greater weight. The data in this study were sourced from the Central Bureau of Statistics for Maluku Province. In this study, the results obtained were a comparison of several Exponential Smoothing methods, namely Simple Exponential Smoothing, Brown Linear Trend, and Holt Linear Trend. The best method

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Febriyanti, Ajeng Nur, and Nur Azizah Komara Rifai. "Metode Triple Exponential Smoothing Holt-Winters untuk Peramalan Jumlah Penumpang Kereta Api di Pulau Jawa." Bandung Conference Series: Statistics 2, no. 2 (2022): 152–58. http://dx.doi.org/10.29313/bcss.v2i2.3560.

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Abstract. Time series analysis is used to predict and formulate future decisions. Structural change is a pattern change that occurs in time series data with a known time of occurrence and unknown when it occurs. Exponential smoothing is a moving average forecasting method by determining the weight exponentially to the observed value. The single exponential smoothing method is used for time series data that does not contain both trend and seasonal patterns. The double exponential method is used for time series data that contains trend patterns but does not contain seasonal patterns. In time ser

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Mayang Sari, Windy Astika, Bachtiar Efendi, and Wan Mariatul Kifti. "ANALISIS PERAMALAN PERSEDIAAN STOK SEPEDA MOTOR BEKAS DENGAN PENERAPAN METODE SES (STUDI KASUS SHOWROOM METRO MOTOR KISARAN)." JUTSI (Jurnal Teknologi dan Sistem Informasi) 2, no. 3 (2022): 205–12. http://dx.doi.org/10.33330/jutsi.v2i3.1903.

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Peramalan (forecasting) merupakan suatu kegiatan untuk meramalkan keadaan dimasa yang akan datang dengan menggunakan pengujian keadaan dimasa lalu. Dalam peramalan terdapat banyak metode yang bisa digunakan, metode yang digunakan dalam penelitian ini adalah metode Single Exponential Smoothing. Metode Single Exponential Smoothing merupakan metode peramalan rata-rata bergerak dimana data akan diberi pembobotan yang canggih tetapi masih mudah untuk digunakan oleh sebuah fungsi exponential.. Adapun parameter waktu yang digunakan dalam meramalkan persediaan stok sepeda motor bekas yaitu alpha 0.1 s

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Setyawan, Heri, Sri Hariyati Fitriasih, and Retno Tri Vulandari. "Implementasi Metode Penghalusan Ekponensial Tunggal Dalam Prediksi Penjualan Buku." Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN) 9, no. 2 (2021): 1. http://dx.doi.org/10.30646/tikomsin.v9i2.539.

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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

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