A Study of Time Series Model for Predicting Jute Yarn Demand: Case Study

Karmaker, C. L.; Halder, Pobitra; Sarker, Eity

doi:10.1155/2017/2061260

Cited by 21 publications

(13 citation statements)

References 13 publications

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“…The triple exponential smoothing method is used when the data shows seasonal trends and behavior [11]. Triple exponential smoothing method is done by using the equation: In forecasting, several methods are applied together, to find the best method in the selection of criteria used by reference to determine the best model [5]. In the forecasting process, whether or not the model used is very influential in the decisions made.…”

Section: Methodsmentioning

confidence: 99%

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Comparison of Forecasting Accuracy Rate of Exponential Smoothing Method on Admission of New Students

2020

jcr

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Forecasting is a tool or technique used to predict or predict a value in the future by paying attention to relevant data or information, both past data or information as well as current data or information. There are several forecasting methods, one of which is the exponential smoothing method. In this study a comparison of forecasting accuracy to new student admission data in a study program at a university using the single exponential smoothing, double exponential smoothing and triple exponential smoothing methods. The best forecasting using the single exponential smoothing method is obtained when the parameter value α = 0.9 with the mean percentage error (MPE) = 0.0239, while the best forecasting using the double exponential smoothing method is obtained when the parameter value α = 0.8 and β = 1, with an MPE value of 0.1172. The best forecasting using the triple exponential smoothing method is obtained when the values of α = 0.6 and β = 0.9, with an MPE value of 0.0161. Based on the forecasting results of the three methods, it was concluded that the best forecasting obtained in this study was to use the triple exponential smoothing method with an MPE value of 0.0161.

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Section: Methodsmentioning

confidence: 99%

“…In forecasting, several methods are applied together, to find the best method in the selection of criteria used by reference to determine the best model [5]. In the forecasting process, whether or not the model used is very influential in the decisions made.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Forecasting Accuracy Rate of Exponential Smoothing Method on Admission of New Students

2020

jcr

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“…The values of MAPE, MAD, and MSE decreased along with increasing smoothing constant value. Research showed that minimum error occurred at constant optimal smoothing ( α = 0.9) which resulted in MAPE of 13.1, MAD of 117.4, and MSD of 26,912.1 ( Karmaker, Halder & Sarker, 2017 ).…”

Section: Literature Reviewmentioning

confidence: 99%

A new model for learning-based forecasting procedure by combining k-means clustering and time series forecasting algorithms

Hartomo

Nataliani

2021

PeerJ Computer Science

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This paper aims to propose a new model for time series forecasting that combines forecasting with clustering algorithm. It introduces a new scheme to improve the forecasting results by grouping the time series data using k-means clustering algorithm. It utilizes the clustering result to get the forecasting data. There are usually some user-defined parameters affecting the forecasting results, therefore, a learning-based procedure is proposed to estimate the parameters that will be used for forecasting. This parameter value is computed in the algorithm simultaneously. The result of the experiment compared to other forecasting algorithms demonstrates good results for the proposed model. It has the smallest mean squared error of 13,007.91 and the average improvement rate of 19.83%.

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“…Prediksi produk yang sepatutnya memainkan peranan penting dalam mengurangi persediaan yang tidak perlu dan merapikan masalah perencanaan yang mengakibatkan peningkatan laba [4]. Saat ini konsep sistem pendukung keputusan untuk berbasis komputer berkembang dan banyak metode yang sangat cepat dapat digunakan untuk membantu proses pengambilan keputusan dengan melakukan pendekatan sistematis [5].…”

Section: Pendahuluanunclassified

Peramalan Penjualan Pupuk Menggunakan Metode Trend Moment

Ulfa

Sumijan

Nurcahyo

2019

INFEB

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Aneka Tani Mandiri Trade Unit is a fertilizer sales shop in the city of Padang. From year to year sales of fertilizers in UD. Aneka Tani Mandiri experiences fluctuations where it is difficult to predict sales increases and decreases every month. The problem that most often occurs in this store is often experiencing shortages and excess stock of goods, this is very likely to occur because many of its items are not sold out and many items are needed by consumers but insufficient stock of goods. Another result is that the profits from the store should be more reduced, with this problem the store must be able to predict how many items will be sold and how many items must be provided in the following month, by knowing the number of items to be sold, the deficiency or excess stock of goods can be avoided. So for that the research was conducted using the Trend Moment Method to predict and predict fertilizer stock that will be provided for the following month. So that will increase sales turnover of the store. By building a fertilizer sales forecasting system using the Trend Moment method which is assisted by the PHP and MySQL programming languages can produce ZA fertilizer sales predictions with success rates above 75%.

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A Study of Time Series Model for Predicting Jute Yarn Demand: Case Study

Cited by 21 publications

References 13 publications

Comparison of Forecasting Accuracy Rate of Exponential Smoothing Method on Admission of New Students

Comparison of Forecasting Accuracy Rate of Exponential Smoothing Method on Admission of New Students

A new model for learning-based forecasting procedure by combining k-means clustering and time series forecasting algorithms

Peramalan Penjualan Pupuk Menggunakan Metode Trend Moment

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