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Journal articles on the topic 'Holt-Winter method'

Author: Grafiati

Published: 7 July 2024

Last updated: 31 July 2025

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1

Andriani, Novita, Sri Wahyuningsih, and Meiliyani Siringoringo. "Application of Double Exponential Smoothing Holt and Triple Exponential Smoothing Holt-Winter with Golden Section Optimization to Forecast Export Value of East Borneo Province." Jurnal Matematika, Statistika dan Komputasi 18, no. 3 (2022): 475–83. http://dx.doi.org/10.20956/j.v18i3.17492.

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Exponential smoothing is one of the short term forecasting methods. The selection of the forecasting method can be done by considering the type of data pattern, such as the Double Exponential Smoothing (DES) Holt method which can be used on trend patterned data and the Triple Exponential Smoothing (TES) Holt-Winter method which can be used on trend and seasonal patterned data. The main problem in using the Holt DES and Holt-Winter TES methods is the parameter selection which is usually done by trial and error, but this method takes a long time so that in this research a more efficient method i

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Santosa, Raden Gunawan, Antonius Rachmat Chrismanto, Willy Sudiarto Raharjo, and Yuan Lukito. "LQ45 Stock Price Forecasting: A Comparison Study of Arima(p,d,q) and Holt-Winter Method." International Journal of Information Technology and Computer Science Applications 2, no. 2 (2024): 115–29. http://dx.doi.org/10.58776/ijitcsa.v2i2.150.

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The Holt-Winter method and ARIMA(p,d,q) are two frequently used forecasting techniques. When using ARIMA, errors are expected to be connected with earlier errors because it is based on data correlation with prior data (autoregressive) (moving average). The Holt-Winter model comes in two different forms: Multiplicative Holt-Winter and Additive Holt-Winter. No one has ever attempted to compare combined time series and cross-section data, despite the fact that there has been a great deal of prior study on ARIMA and Holt-Winter. In a combined time-series and cross-section dataset, the accuracy rat

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Khusrul, Kurniawan, and Madelan Sugiyono. "Forecasting Using Time Series Analysis Method in Crypto Currency Period 2015 – 2022." International Journal of Innovative Science and Research Technology 7, no. 9 (2022): 1454–59. https://doi.org/10.5281/zenodo.7201582.

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Cryptocurrency is a digital currency that is currently much interested as an alternative investment. ARIMA, GARCH, and Holt's Winter method are one of the methods used for forecasting time series data. This research aims to create a model and predict the price of bitcoin. The data used is secondary data in the form of daily closing price data for Bitcoin, Ripple, and Litecoin, as much as 2,520 daily closing price data starting from August 07, 2015 to June 30, 2022, to predict Bitcoin, Ripple, and Litecoin prices for the following 30 periods starting on July 01, 2022 to July 31, 2022. This

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Saeful, Aji, Fandy Setyo Utomo, Yuli Purwati, and Mohd Sanusi Azmi. "COMPARATIVE ANALYSIS OF EXPONENTIAL SMOOTHING MODELS FOR SALES PREDICTION AND SUPPLY MANAGEMENT IN E-COMMERCE." JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) 10, no. 1 (2024): 152–59. http://dx.doi.org/10.33480/jitk.v10i1.5035.

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In the growing era of e-commerce, stock management is crucial. Problems arise in forecasting sales in order to achieve effective stock management. This research uses the time series analysis method by focusing on comparing the accuracy of three forecasting methods: Single Exponential Smoothing (SES), Double Exponential Smoothing (DES), and Triple Exponential Smoothing (TES/Holt-Winter). This research provides a solution by comparing the performance of the three methods based on the Mean Absolute Error (MAE) results and prediction graphs. The goal is to determine the most accurate forecasting m

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Septiana, Dian. "Forecasting Rice Prices with Holt-Winter Exponential Smoothing Model." Hanif Journal of Information Systems 1, no. 2 (2024): 62–67. http://dx.doi.org/10.56211/hanif.v1i2.17.

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Rice, as a staple food, plays a crucial role in global food security. Accurate forecasting of rice prices is essential for policymakers, farmers, and consumers alike. This article explores the application of the Holt-Winter exponential smoothing model to predict rice prices. Holt-Winter method is chosen for its ability to capture both trend and seasonality in time series data, which are prominent features in agricultural commodity prices such as rice. The study analyzes historical price data, identifies trends, seasonality, and incorporates smoothing parameters in additive and multiplicative m

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Jaber, Abobaker M., Mohd Tahir Ismail, and Alsaidi M. Altaher. "Application of Empirical Mode Decomposition with Local Linear Quantile Regression in Financial Time Series Forecasting." Scientific World Journal 2014 (2014): 1–5. http://dx.doi.org/10.1155/2014/708918.

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This paper mainly forecasts the daily closing price of stock markets. We propose a two-stage technique that combines the empirical mode decomposition (EMD) with nonparametric methods of local linear quantile (LLQ). We use the proposed technique, EMD-LLQ, to forecast two stock index time series. Detailed experiments are implemented for the proposed method, in which EMD-LPQ, EMD, and Holt-Winter methods are compared. The proposed EMD-LPQ model is determined to be superior to the EMD and Holt-Winter methods in predicting the stock closing prices.

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Damaliana, Aviolla Terza, Kartika Maulida Hindrayani, and Tresna Maulana Fahrudin. "Hybrid Holt Winter-Prophet method to forecast the num-ber of foreign tourist arrivals through Bali's Ngurah Rai Airport." Internasional Journal of Data Science, Engineering, and Anaylitics 3, no. 2 (2024): 21–32. http://dx.doi.org/10.33005/ijdasea.v3i2.8.

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The Indonesian is an archipelago rich in culture and natural resources. The Government of Indonesia utilizes this wealth by maximizing the tourism potential to earn sizeable foreign exchange. As a major destination, the Indonesian government needs a strategy to ensure foreign tourists continue to increase in terms of health, cleanliness, a sustainable environment and infrastructure. When we can forecast the number of foreign tourists, it is hoped that the government can establish appropriate policies to develop tourism. Based on this, an appropriate forecasting method is needed. This study wil

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Mufarroha, Fifin Ayu, Akhmad Tajuddin Tholaby, Devie Rosa Anamisa, and Achmad Jauhari. "Prediction Model for Tourism Object Ticket Determination in Bangkalan, Madura, Indonesia." ComTech: Computer, Mathematics and Engineering Applications 14, no. 2 (2023): 69–81. http://dx.doi.org/10.21512/comtech.v14i2.7992.

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One of the regencies in Madura, namely Bangkalan, with its local wisdom and beautiful landscapes has the potential to become a tourism center. However, there may be a decrease in the number of visits caused by some factors. The research used the time series method to build a prediction model for tourist attraction entrance tickets. The model development aimed to estimate the number of tourist attraction visits in the future. The right model was needed to get the best prediction results. Least square, Holt-Winter, Seasonal Autoregressive Integrated Moving Average (SARIMA), and Rolling were chos

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Utami, Ruli, and Suryo Atmojo. "Perbandingan Metode Holt Eksponential Smoothing dan Winter Eksponential Smoothing Untuk Peramalan Penjualan Souvenir." Jurnal Ilmiah Teknologi Informasi Asia 11, no. 2 (2017): 123. http://dx.doi.org/10.32815/jitika.v11i2.191.

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UD. Fajar Jaya is a trading business unit engaged in the supply of souvenirs. But in the management of the business there are some problems of which are UD. Fajar Jaya can not predict how the optimal number of souvenirs that must be provided to customers on every item souvenirs are sold. This causes the service to consumers less than the maximum, especially at certain moments sales of souvenirs (example: glass souvenirs) jumped dramatically from the number of average sales. To overcome the above, the authors propose to forecast the level of sales of souvenirs using Holt and Winter methods that

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Salamiah, Mia, Sukono Sukono, and Eddy Djauhari. "Prediction of the Number of Visitors to Tourism Objects in the Ujung Genteng Coastal Area of Sukabumi Using the Holt-Winter Method." Operations Research: International Conference Series 2, no. 4 (2021): 109–16. http://dx.doi.org/10.47194/orics.v2i4.184.

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Ujung Genteng Sukabumi Beach is one of the tourism destinations in Sukabumi Regency, West Java. Forecasting tourist arrivals is a very important factor for tourist destination policies and contributes to the regional economy and the surrounding community. The purpose of this study is to predict the number of tourists who come to Ujung Genteng Beach, Sukabumi. The method used is the Holt-Winter approach exponential smoothing. The Holt-Winter method is used for data that is not stationary, has both trend and seasonal elements. The Holt-Winters method has two models, namely the Additive model and

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Fauzi, Nur Fatihah, Nurul Shahiera Ahmadi, Nor Hayati Shafii, and Huda Zuhrah Ab Halim. "A Comparison Study on Fuzzy Time Series and Holt-Winter Model in Forecasting Tourist Arrival in Langkawi, Kedah." Journal of Computing Research and Innovation 5, no. 1 (2020): 34–43. http://dx.doi.org/10.24191/jcrinn.v5i1.138.

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The tourism industry in Malaysia has been growing significantly over the years. Tourism has been one of the major donors to Malaysia’s economy. Based on the report from the Department of Statistics, a total of domestic visitors in Malaysia were recorded at about 221.3 million in 2018 with an increase of 7.7% alongside a higher record in visitor arrivals and tourism expenditure. This study aims to make a comparison between two methods, which are Fuzzy Time Series and Holt-Winter in forecasting the number of tourist arrival in Langkawi based on the monthly tourist arrival data from January 2015

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Sucipto, Lalu, and Syaharuddin Syaharuddin. "Konstruksi Forecasting System Multi-Model untuk pemodelan matematika pada peramalan Indeks Pembangunan Manusia Provinsi Nusa Tenggara Barat." Register: Jurnal Ilmiah Teknologi Sistem Informasi 4, no. 2 (2018): 114. http://dx.doi.org/10.26594/register.v4i2.1263.

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Penelitian ini bertujuan untuk mengembangkan produk Forecasting System Multi-Model (FSM) guna menentukan metode terbaik dalam sistem peramalan (forecast) dengan mengkonstruksi beberapa metode dalam bentuk Graphical User Interface (GUI) Matlab dengan menghitung semua indikator tingkat akurasi guna menemukan model matematika terbaik dari data time series pada periode tertentu. Pada tahap simulasi, tim peneliti menggunakan data Indeks Pembangunan Manusia (IPM) Provinsi Nusa Tenggara Barat (NTB) tahun 2010-2017 guna memprediksi IPM NTB tahun 2018. Adapun metode yang diuji adalah Moving Average (SM

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Lê, Đức Đạo, and Linh Chi Phạm. "Forecasting market demand using ARIMA and Holt - Winter method: A case study on canned fruit production company." TẠP CHÍ KHOA HỌC TRƯỜNG ĐẠI HỌC QUỐC TẾ HỒNG BÀNG 4 (June 24, 2023): 1–8. http://dx.doi.org/10.59294/hiujs.vol.4.2023.380.

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Consumer demand is an important factor in any business, especially in the food retail industry whose products are perishable and have a short life cycle. The daily demand for a food product is affected by external factors, such as seasonality, price reduction and holidays. To satisfy the stochastic demand, product characteristics vary with customer are required to be timely updated based on market dynamicity. According to previous research, to choose suitable forecasting model is the main concern of enterprises on demand management issue. Proper demand forecasting provides organization with va

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Zhao, Yangyuhui. "Research and Forecasting of the FTSE100 Index over Long Time Series." Advances in Economics, Management and Political Sciences 86, no. 1 (2024): 133–42. http://dx.doi.org/10.54254/2754-1169/86/20240887.

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In order to research the UK and Global stock market, FTSE100 index is one of the most important values to study. This paper uses several models to forecast the future curve of the FTSE100 and compare these models to find a best way on forecasting. Then by analyzing the timeseries, the author shows several factors that might affect the timeseries which will be useful on the further forecast of the market. By using the simple forecast method, including Mean, Nave, Snaive and Drift, Holt and Holt-winter model, and ARIMA model on the closing price of FTSE100 from Feb.2004 to Feb.2024. The result s

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Pertiwi, Dewi Darma. "Applied Exponential Smoothing Holt-Winter Method for Predict Rainfall in Mataram City." Journal of Intelligent Computing and Health Informatics 1, no. 2 (2020): 45. http://dx.doi.org/10.26714/jichi.v1i2.6330.

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Weather conditions in the city of Mataram tend to be erratic and difficult to predict, such as the condition of rainfall data in 2018 which changes over a certain period of time so that the weather is difficult to predict accurately. In this study, we propose the Exponential Smoothing Holt-Winter method to forecast rainfall in the city of Mataram, so that it can be a decision support for various interested sectors. This method has been tested using secondary data from the Mataram City Central Bureau of Statistics for the period January 2014 to 2018 and evaluated using Mean Absolute Deviation (

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Setiawan, Dwi, Eko Sediyono, and Irwan Sembiring. "Pemanfaatan Metode Association Rules dan Holt-Winter Multiplicative untuk Meningkatkan Peluang Penjualan Obat Pertanian." JURNAL SISTEM INFORMASI BISNIS 10, no. 1 (2020): 46–55. http://dx.doi.org/10.21456/vol10iss1pp46-55.

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The competition level between companies on executing product marketing is rapidly increasing, so the companies have to understand the importance of correlation between external environments of company with consumer’s needs. One of the efforts that can be done is by utilizing data warehouse and the application of infrastructure in information and technology field. This research combined Association Rules method to extracting pattern and finding every possibility that potential to increase sales and Holt-Winter Multiplicative method to estimate the alteration of trend on the seasonal data. After

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Nurdini, Arief, and Ardhy Lazuardy. "ANALYSIS OF DEMAND FORECASTING FOR TEMPEH PRODUCTS AT INDONESIAN TEMPEH HOUSES USING THE HOLT-WINTERS ADDITIVE METHOD APPROACH." International Journal Science and Technology 2, no. 1 (2023): 59–64. http://dx.doi.org/10.56127/ijst.v2i1.854.

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Rumah Tempe Indonesia is an MSME engaged in processing soybeans into tempeh products. The production system used is made to stockThis production system can cause problems, including the amount of production that does not match consumer needs, causing a shortage or excess of products which are very inefficient for the company's business continuity. For this reason, a study was carried out to determine the forecast for the demand for GMO Tempe at Indonesian Tempe Houses for the next 12 periods using the Holt-winters method and to determine the accuracy of the forecast made. The method used in th

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Amalia, Iva Rizki, Tatik Widiharih, and Tarno Tarno. "HOLT WINTERS EXPONENTIAL SMOOTHING UNTUK MERAMALKAN PRODUK DOMESTIK BRUTO DI INDONESIA." Jurnal Gaussian 13, no. 1 (2024): 219–29. http://dx.doi.org/10.14710/j.gauss.13.1.219-229.

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A country's economic growth will be seen as having grown better or worse than in the past by measuring based on the increase in Gross Domestic Product (GDP). The pattern of Indonesian GDP from 2010 to 2022 shows that the data increases from year to year and there are seasonal fluctuations in the quarter. Holt Winters method is part of the Exponential Smoothing method used for forecasting if the data shows a trend and seasonality in the data pattern. The Holt Winters method has two models, namely additive and multiplicative. Holt Winters Additive is used if the data shows trends and seasonal pa

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Heshu Othman Faqe, Ayad Otham Hamdin, and Mohammad Mahmood Faqe Hussein. "Forecasting Cotton Production in Iraq during the years (1960-2022) using Markov Chain Approach and Holt-Winter Method." Tikrit Journal of Administrative and Economic Sciences 20, no. 66, part 2 (2024): 318–33. http://dx.doi.org/10.25130/tjaes.20.66.2.18.

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Cotton is a fibrous material derived from the seed pods of the cotton plant (Gossypium). It is a natural fiber extensively utilized in the textile industry for the manufacturing of items like clothing, linens, and other fabric-based products. Valued for its breathability, absorbency, and adaptability, cotton is a widely chosen material for diverse everyday goods. Two models are used in this study, such as the Markov chain approach and the Holt-Winter method, to forecast cotton production in Iraq over the years 1960–2022. A Markov chain approach model is a accurate framework describing a series

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Narayana, I. Putu Edward, and Yuanita Handayati. "Proposed Improvement of Demand Forecast Accuracy using Six Sigma DMAIC in PT XYZ." Jurnal Studi Manajemen dan Bisnis 10, no. 2 (2023): 157–63. http://dx.doi.org/10.21107/jsmb.v10i2.23120.

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This research aimed to optimizing strategies for PT XYZ, specifically focusing on bridging the gaps between demand forecasts and actual market demand of lubricants product, with a strong emphasis on the Business-to-Business (B2B) segment. B2B introduces unique challenges, necessitating a specialized approach. Employing the Six Sigma DMAIC methodology, a comprehensive analysis is conducted to uncover deficiencies in current sales forecasting methods. The Holt-Winter method is then applied to offer robust remedies, effectively minimizing complexities such as seasonal patterns and market trends.

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Azma, Meil Sri Dian, Dony Permana, Fadhilah Fitri, and Atus Amadi Putra. "Comparison Of Extreme Learning Machine And Holt Winter’s Exponential Smoothing Methods In Railway Passenger Forecasting." UNP Journal of Statistics and Data Science 2, no. 3 (2024): 366–72. http://dx.doi.org/10.24036/ujsds/vol2-iss3/211.

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Trains are public transportation consisting of a locomotive pulled by other carriages as its main part. The carriages are very large so that they can transport passengers and goods on a large scale. Forecasting is a process to estimate how much future demand will be which includes the needs in terms of quantity, quality, time, and location needed to meet the demand for goods or services. The method used in forecasting this problem is Holt Winter Exponential Smoothing. The Holt Winter method is a moving average forecasting method that gives weight to past data exponentially so that current data

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Frederick, Ojiemhende Ehiagwina, Olashile Afolabi Lateef, Mustapha Khadijat, Raheem Kabirat, Jamiu Jibola Anifowose, and O. Salaudeen Wasiu. "A Study on the Performance of GA-Holt-Winters Model in 900 MHz Spectrum Prediction." International Journal of Novel Research in Electrical and Mechanical Engineering 9, no. 1 (2022): 23–31. https://doi.org/10.5281/zenodo.6832380.

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<strong>Abstract:</strong> Continuous spectrum measurement is expensive and time consuming. This has necessitated the concept of spectrum prediction. Spectrum prediction uses historically observed data from spectrum sensing to forecast future channel states. In this research the suitability of the genetic algorithm modified Holt-Winters exponential model in the prediction of spectrum occupancy data was investigated. Minute spectrum duty cycle of selected locations in Ilorin, Nigeria was used in the evaluation of the forecast behaviour of the methods. It was observed that GA-Holt-Winter techniq

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Firmanto, Devit Hari, Eko Prasetyo, and Mas Nurul Hamidah. "Instant Cement Forming Using Holt-Winter (case Study: CV Trijaya Abadi)." JEECS (Journal of Electrical Engineering and Computer Sciences) 3, no. 1 (2018): 389–94. http://dx.doi.org/10.54732/jeecs.v3i1.145.

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CV.Trijaya Abadi is an industry that produces cement, and make various innovations by producing instant cement. Itis often the case with errors in doing the forecasting is if the amount of production is produced too much while thedemand is small it will cause losses for the company as well as vice versa if the demand a lot while the productionwill be a bit disappointment of consumers resulting in the company losing konsakuya. know the amount of instantcement production in the next period. The method used for forecasting in this research is Exponential SmoothingHolt-Winters method with multiply

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Aribowo, Anung B., Dedy Sugiarto, Iveline Anne Marie, and Jeany Fadhilah Agatha Siahaan. "Peramalan harga beras IR64 kualitas III menggunakan metode Multi Layer Perceptron, Holt-Winters dan Auto Regressive Integrated Moving Average." Ultimatics : Jurnal Teknik Informatika 11, no. 2 (2020): 60–64. http://dx.doi.org/10.31937/ti.v11i2.1246.

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This paper aims to present the analysis of price movements of IR64 quality III at the Cipinang Rice Main Market (PIBC) and the accuracy comparison of forecasting using Multi Layer Perceptron (MLP), Holt-Winters, and Auto Reggressive Integrated Moving Average (ARIMA) method. The data are daily price from 1 January 2016 to 31 May 2018 sourced from PT. Food Station. The analysis shows that the price of IR64 quality III rice tends to rise towards the end of 2016 and 2017. This is related to the decrease in the level of rice supply by January each year which encourages PT Food Station to conduct ma

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Rani Reddy, Dr M. "Forecasting Railway Passengers Demand Using Holt-Winter Method With R Statistical Tool." International Journal of Advanced Multidisciplinary Scientific Research 2, no. 8 (2020): 1–8. http://dx.doi.org/10.31426/ijamsr.2019.2.8.1811.

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Agustino, Gerson Togar Manurung, and Sugiyono Sugiyono. "Forecasting of Southeast Sulawesi Nickel Ore Production using Arima & Holt-Winter Method." International Journal of Innovative Science and Research Technology 7, no. 1 (2022): 338–45. https://doi.org/10.5281/zenodo.5910629.

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Nickel is an important metal element in the battery cell components used for electric cars. For the manufacture of batteries, three main raw materials are needed, namely nickel, lithium and cobalt. For nickel, Indonesia controls 30 percent. Compared to some other countries.From the results of experiments conducted by the author, it was found that the most accurate forecasting for nickel ore production data is the ARIMA forecasting method. The results obtained from nickel ore forecasts that there will be a decline after 2020. This is not a good thing for the government's plan to increase el

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Andayani, Puji. "Implementation of Holt-Winter Exponential Smoothing Method to Forecast The Spread of Covid-19." Indonesian Journal of Mathematics and Applications 1, no. 2 (2023): 13–24. http://dx.doi.org/10.21776/ub.ijma.2023.001.02.2.

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This research examines the Holt winters exponential smoothing method to solve forecasting problems using case studies of the spread of Covid-19. The data source uses the transmission of Covid-19 in Indonesia. MAPE is used to measure errors in data forecasting. The results are structured to serve as a recommendation for other researchers in choosing a method for predicting the spread of the disease. Based on the results, forecasting with the Holt-Winters model in positive cases produces a MAPE value of 9.21% using the Multiplicative model and the best parameter values of alpha, beta and gamma (

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Ade Onny Siagian. "Struktur Peramalan System Multi-Model untuk pemodelan matematika pada Forecast Indeks Pembangunan Manusia Provinsi Bali." DIAJAR: Jurnal Pendidikan dan Pembelajaran 1, no. 1 (2022): 86–94. http://dx.doi.org/10.54259/diajar.v1i1.204.

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The purpose of this research is to develop a product was called Forecasting System Multi-Model (FSM) to determine the best method in the forecasting system by constructing several methods in the form of Graphical User Interface (GUI) Matlab. It was done by all indicator accuration to find the best mathematical model of time series data in a certain period. In the simulation phase, this research used the Human Development Index (HDI) data of Bali Province in 2010 - 2017 to predict the HDI data of Bali in 2018. The methods tested were Moving Average (SMA, WMA and EMA), Exponential Smoothing Meth

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Mohamed, Elmubarak. "Implementation Hybrid (NIDS) System using Anomaly Holt-winter Algorithm and Signature based Scheme." International Journal of Advances in Scientific Research and Engineering (ijasre) 5, no. 6 (2019): 141–48. https://doi.org/10.31695/IJASRE.2019.33278.

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An intrusion detection system is a security attack detection/prevention mechanism, it can be implemented into the software module or hardware module for the purpose of monitoring the systems or network for malicious activities. IDS can be categorized by monitoring resources to Host Intrusion Detection System (HIDS) and Network Intrusion Detection System (NIDS). HIDS are deployed to monitor local activities on the specific machine; on the other hand, NIDS placed into the central point on the network such as firewall to monitor network traffic. IDS also can be categorized depending on the detect

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Razi, Zulfa, Mirunnisa Mirunnisa, Maryanti Maryanti, and Nurhayati Nurhayati. "PERAMALAN NILAI TUKAR PETANI PROVINSI ACEH: DITINJAU DENGAN METODE DOUBLE EXPONENTIAL SMOOTHING DAN HOLT WINTER." Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika 5, no. 2 (2024): 974–82. http://dx.doi.org/10.46306/lb.v5i2.703.

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This research aimed to compare the performance of the Double Exponential Smoothing and Holt-Winter methods in forecasting the Farmer Exchange Rate (NTP) for the Horticulture Farmer Subsector in Aceh Province. Secondary data on the NTP for the Aceh Horticulture Subsector from 2020-2023 was obtained from the Aceh Provincial Central Statistics Agency (BPS) website. The data processing was carried out using the R software. The results showed that the Double Exponential Smoothing method had a Root Mean Squared Error (RMSE) of 3.413201, a Mean Absolute Percentage Error (MAPE) of 2.85835, and a Mean

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Dwipurwani, Oki, Fitri Maya Puspita, Suzlin Supadi, Evi Yuliza, and Dhiya Qatrunnada. "HOLT-WINTER METHOD FOR FORECASTING LIQUID ALUMINUM SULFATE USAGE FOR PROBABILISTIC INVENTORY MODELING Q WITH ERLANG DISTRIBUTION." BAREKENG: Jurnal Ilmu Matematika dan Terapan 19, no. 1 (2025): 453–64. https://doi.org/10.30598/barekengvol19iss1pp453-464.

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Water is a natural resource important for life and daily activities. Water distributed by the Regional Drinking Water Company (PDAM) should include a coagulation process using liquid aluminum sulfate as a coagulant before it can be consumed. Therefore, this research aims to predict the need for liquid aluminum sulfate in PDAM from 2023 to 2024 using Holt-Winter's method. It also aims to evaluate the optimum liquid aluminum sulfate chemical inventory policy using Q probabilistic inventory model with Normal and erlang probabilistic distributions in PDAM. The data was obtained from Tirta Musi PDA

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Rahman, Abdul, Dyah Alfa Sa'adah Al-adawiyyah, Muli ana, Syil Viya Rivika, Arisman Adnan, and Rado Yendra. "Holt-Winter Forecasting Method for Inflow and Outflow of Bank Indonesia in Riau." International Journal of Economics and Management Studies 8, no. 7 (2021): 71–76. http://dx.doi.org/10.14445/23939125/ijems-v8i7p108.

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Elmunim, Nouf Abd, Mardina Abdullah, Alina Hasbi, and Siti Aminah Bahari. "Investigation on the Implementation of the Holt-Winter Method for Ionospheric Delay Forecasting." Advanced Science Letters 23, no. 2 (2017): 1325–28. http://dx.doi.org/10.1166/asl.2017.8356.

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Nandi, Biplob Kumar, Muntasir Chaudhury, and Gazi Quamrul Hasan. "Univariate Time Series Forecasting: A Study on Monthly Tax Revenue of Bangladesh." EAST WEST JOURNAL OF BUSINESS AND SOCIAL STUDIES 4 (July 28, 2015): 1–28. http://dx.doi.org/10.70527/ewjbss.v4i.113.

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In recent years, Bangladesh has taken various steps to modernize tax system in order to enhance tax effort. Due to subsequent increase in financial constraints globally, economy's reliance on domestic resource mobilization continues to intensify. As a result, tax revenue target for every forthcoming budget appears to be buoyant albeit the prevalence of domestic constraints, i.e. inefficiencies in tax system, narrower tax base along with numerous exemptions and political instability. To enhance tax effort to reduce fiscal vulnerability, a esoteric revenue forecasting procedure is necessary. But

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Salauddin Khan, Md, Masudul Islam, Sajal Adhikary, Md Murad Hossain, and Sohani Afroja. "Analysis and Predictions of Seasonal Affected Weather Variables of Bangladesh: SARIMA Models vs. Traditional Models." International Journal of Business and Management 13, no. 12 (2018): 70. http://dx.doi.org/10.5539/ijbm.v13n12p70.

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Bangladesh is a semi-tropical country, categorized by widespread seasonal disparities in rainfall, temperature, and humidity. Seasonality has been an input aspect of time series modeling when taking into account weather variables. In terms of multiple features of the weather variables i.e. randomness, cyclical variation and trend, time series methods etc. ARIMA can be a superior preference but, weather variables are affected by seasonality. Thinking about the grimy meadow, this paper presents Seasonal Auto-regressive Moving Average (SARIMA) model that takes seasonal and cyclical variation over

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Diksa, I. Gusti Bagus Ngurah. "Forecasting the Existence of Chocolate with Variation and Seasonal Calendar Effects Using the Classic Time Series Approach." Jurnal Matematika, Statistika dan Komputasi 18, no. 2 (2022): 237–50. http://dx.doi.org/10.20956/j.v18i2.18542.

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Chocolate is the raw material for making cakes, so consumption of chocolate also increases on Eid al-Fitr. However, this is different in the United States where the tradition of sharing chocolate cake is carried out on Christmas. To monitor the existence of this chocolate can be through the movement of data on Google Trends. This study aims to predict the existence of chocolate from the Google trend where the use of chocolate by the community fluctuates according to the calendar variance and seasonal rhythm. The method used is classic time series, namely nave, double exponential smoothing, mul

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Ponziani, Regi Muzio. "Foreign Tourists Arrival Forecasting at Major Airports in Indonesia:." IJEBD (International Journal of Entrepreneurship and Business Development) 4, no. 5 (2021): 662–70. http://dx.doi.org/10.29138/ijebd.v4i5.1507.

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Purpose: This research purports to forecast the number of foreign tourists arriving at major airport in Indonesia. The airports chosen are Soekarno Hatta, Juanda, I Gusti Ngurah Rai, and Kualanamu international airports. Design/methodology/approach: The data used were foreign tourists arrival at major airports located in Jakarta, Surabaya, Medan, and Denpasar. The data extended from January 2014 until December 2018. Two time-series methods were employed, namely Holt-Winter Seasonality and Exponential Smoothing with maximum likelihood. The forecasts would reveal the fitted numbers of fore

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Andi Bimantoro, Fanji, Sugiyono Madelan, and Ahmad Badawi Saluy. "Forecasting With Time Series Method at PT. RSM in Bekasi Jawa Barat." Dinasti International Journal of Economics, Finance & Accounting 2, no. 3 (2021): 273–82. http://dx.doi.org/10.38035/dijefa.v2i3.858.

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This study aims to determine the most valid forecasting method based on the time series method. This research uses a quantitative descriptive method, the research variable is sales data of MT products belonging to PT. RSM period August 2018 to January 2021. Data processing using Microsoft excel and Minitab 19 software. ABC analysis results show product codes RSM020, RSM021, and RSM017 occupy the three highest ranks in class A by contributing 26.16% sales figures. Based on the forecasting results using various time series methods (linear trend, decomposition, moving average, single exponential

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AL Yarubi, Mansoor, Nur Arina Bazilah Kamisan, and Siti Mariam Norrulashikin. "Modeling and forecasting emergency department crowding using SARIMA, Holt Winter method, and Prophet models." International journal of health sciences 9, no. 1 (2025): 230–43. https://doi.org/10.53730/ijhs.v9n1.15567.

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Emergency department (ED) crowding in health care is linked with longer wait times, high mortality rates, and low healthcare quality. Univariate time series models such as Seasonal Autoregressive Integrated Moving Average (SARIMA), Holt-Winters method (HW), and Prophet model (PM) have been widely employed to predict ED crowding. However, there is no consensus on the best fit time series model for ED crowding forecasting. This study compared the predictive precision of three univariate time series models, SARIMA, HW, and PM, in predicting ED crowding at Nizwa Hospital in Oman. The study used ho

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Sari, I. K., Liyantono, and M. Solahudin. "Comparative study of oil palm productivity estimation models: multilinear regression and holt-winters approach." IOP Conference Series: Earth and Environmental Science 1386, no. 1 (2024): 012031. http://dx.doi.org/10.1088/1755-1315/1386/1/012031.

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Abstract Oil palm plays a crucial role in Indonesia’s economy through the increased production and export of oil palm. However, managing and predicting productivity in expanding oil palm plantations presents significant challenges. Current estimation methods are resource-intensive and time-consuming. This study advocates the application of remote sensing techniques, particularly through Google Earth Engine and Landsat 8 satellite imagery, for efficient oil palm productivity estimation. Using a multilinear regression model that integrates the Normalized Difference Vegetation Index (NDVI) and ra

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Bayu, Gede Eridya, I. Ketut Gede Darma Putra, and Ni Kadek Dwi Rusjayanthi. "A Comparison Between Backpropagation, Holt-Winter, and Polynomial Regression Methods in Forecasting Dog Bites Cases in Bali." Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) 9, no. 3 (2021): 251. http://dx.doi.org/10.24843/jim.2021.v09.i03.p06.

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Rabies is a zoonotic disease that is usually transmitted to humans through animal bites. It can cause severe damage to the central nervous system and is generally fatal. Dog bite cases are considered the leading cause of rabies transmission in Bali. The government's preventive action is expected to reduce the problem of increasing the number of dog bite cases so that it does not spread quickly and cause casualties. Data mining is an attempt to extract knowledge from a set of data. The use of data mining in this study is to forecast the number of dog bite cases in Bali. Forecasting predicts wha

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Rosita, Yesy Diah, and Lady Silk Moonlight. "Perbandingan Metode Prediksi untuk Nilai Jual USD: Holt-Winters, Holt's, dan Single Exponential Smoothing." JTIM : Jurnal Teknologi Informasi dan Multimedia 5, no. 4 (2024): 322–33. http://dx.doi.org/10.35746/jtim.v5i4.473.

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In the ever-changing landscape of the global economy, the role of the United States Dollar (USD) as the backbone of the international financial system significantly influences market stability and dynamics. The close correlation between fluctuations in the USD exchange rate and internal and external factors demands effective prediction methods to understand and manage associated risks. This study aims to compare the performance of three main prediction methods: Single Exponential Smoothing (SES), Holt's Method, and Holt-Winters Method, in forecasting USD exchange rates. Utilizing historical da

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Aini, Novi Nur, Atiek Iriany, Waego Hadi Nugroho, and Faddli Lindra Wibowo. "Comparison of Adaptive Holt-Winters Exponential Smoothing and Recurrent Neural Network Model for Forecasting Rainfall in Malang City." ComTech: Computer, Mathematics and Engineering Applications 13, no. 2 (2022): 87–96. http://dx.doi.org/10.21512/comtech.v13i2.7570.

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Rainfall forecast is necessary for many aspects of regional management. Prediction of rainfall is useful for reducing negative impacts caused by the intensity of rainfall, such as landslides, floods, and storms. Hence, a rainfall forecast with good accuracy is needed. Many rainfall forecasting models have been developed, including the adaptive Holt-Winters exponential smoothing method and the Recurrent Neural Network (RNN) method. The research aimed to compare the result of forecasting between the Holt-Winters adaptive exponential smoothing method and the Recurrent Neural Network (RNN) method.

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Sato, Enos Nobuo, Carlos Teixeira, Beck Nader, and Giorgio de Tomi. "Time Series Models to Obtain the Barrel Crude Oil Prices." Materials Science Forum 805 (September 2014): 422–28. http://dx.doi.org/10.4028/www.scientific.net/msf.805.422.

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The use of time series as an additional tool in decision making for the oil industry has been established as a mechanism for predicting the behavior of crude oil price. Especially in Brazil, after the discovery in this decade of the pre-salt reservoirs, the estimate of the price of a crude oil barrel through the use of modern techniques can minimize risks in exploration and production of oil. The more appropriate pricing for crude oil aims to minimize the risks to the economic activity for both exporters and importers of oil. This paper presents six different methods for obtaining crude oil fu

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Nurdyah, Himda Anataya, Betty Subartini, and Sukono Sukono. "Investment Portfolio Optimization Using the Mean-Variance Model Based on Holt-Winters Stock Price Forecasting of Food Sector in Indonesia." International Journal of Quantitative Research and Modeling 6, no. 2 (2025): 264–74. https://doi.org/10.46336/ijqrm.v6i2.1017.

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The importance of the food sector to Indonesia's economy makes it one of the most attractive sectors to consider in an investment portfolio. An optimal portfolio is the best choice for investors among various efficient portfolios, aiming to maximize returns while minimizing risk. Moreover, since investment is inherently associated with fluctuating stock prices, accurate forecasting is necessary to anticipate future stock movements. This study aims to accurately predict stock prices and construct an optimal portfolio consisting of five food sector stocks listed on the Indonesia Stock Exchange,

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Elmunim, N. A., M. Abdullah, A. M. Hasbi, and S. A. Bahari. "Comparison of GPS TEC variations with Holt-Winter method and IRI-2012 over Langkawi, Malaysia." Advances in Space Research 60, no. 2 (2017): 276–85. http://dx.doi.org/10.1016/j.asr.2016.07.025.

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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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Shaleh, W., Rasim, and Wahyudin. "The System of Inventory Forecasting in PT. XYZ by using the Method of Holt Winter Multiplicative." IOP Conference Series: Materials Science and Engineering 288 (January 2018): 012152. http://dx.doi.org/10.1088/1757-899x/288/1/012152.

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Tasia, Ena, Nanda Nazira, Qurotul A’yuniyah, M. Hayatul Fikri, and Andri Nofiar Am. "Analisis Model Manajemen Permintaan SCM dan Peramalan Penjualan Busana Menggunakan Metode Holt-Winter Exponential Smoothing." Jurnal Teknik Industri Terintegrasi 6, no. 4 (2023): 1303–12. http://dx.doi.org/10.31004/jutin.v6i4.20313.

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Sales forecasting is a highly crucial strategy in the business world, as it significantly contributes to enhancing a company's profits. In this context, sales transaction forecasting plays a vital role in assisting business decision-makers in planning effective sales strategies. The utilization of the Holt-Winters Exponential Smoothing method in sales forecasting demonstrates an effective approach. In this study, this method was applied to retail sales data of Muslim clothing from 2021 to 2023. By setting the parameters ? = 0.9, ? = 0.1, and ? = 0.1, the forecasting results indicate a high lev

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Aziz, Rahmah. "Peramalan Jumlah Penumpang di Bandar Udara Soekarno-Hatta dengan menggunakan Pemulusan Eksponensial Tripel tipe Holt-Winter dan tipe Brown." Journal of Mathematics UNP 7, no. 3 (2022): 63. http://dx.doi.org/10.24036/unpjomath.v7i3.12524.

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The main airports in Indonesia, including at Soekarno-Hatta, are deserted, due to government policies to overcome the Covid-19 disease outbreak. The number of passengers has fallen drastically, every month the plane is erratic in carrying passengers. With a pandemic like this, the airline must make a strategy to avoid losses. To overcome this problem, the purpose of this study is to predict the number of passengers at Soekarno-Hatta Airport during the pandemic using triple exponential smoothing of Brown type and Holt-Winter type. In the triple exponential smoothing method, trend analysis is ca

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