A Medical Disposable Supply Demand Forecasting By Moving Average And Exponential Smoothing Method

PT Kujang Utama Antasena is a shoe industry company specifically for security. The purpose of this study is to forecast or predict sales. This study uses a quantitative method with exponential smoothing, smoothing factor/constant (?) of 0.2. In production activities, forecasting is carried out to determine the amount of demand for a product and is the first step of the production planning and control process to reduce uncertainty so that an estimate that is close to the actual situation is obtained. The exponential smoothing method is a moving average forecasting method that gives exponential or graded weights to the latest data so that the latest data will get a greater weight. In other words, the newer or more current the data, the greater the weight.

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PERBANDINGAN METODE SINGLE EXPONENTIAL SMOOTHING DAN MOVING AVERAGE PADA PERAMALAN PENJUALAN PRODUK MINYAK GORENG DI PT TUNAS BARU LAMPUNG

JURNAL REKAYASA SISTEM INDUSTRI ◽

10.33884/jrsi.v6i2.3694 ◽

2021 ◽

Vol 6 (2) ◽

pp. 101

Author(s):

Niken Chaerunnisa ◽

Ade Momon

Keyword(s):

Moving Average ◽

Exponential Smoothing ◽

Smoothing Method ◽

Oil Products ◽

Cooking Oil ◽

Forecasting Method ◽

Double Exponential Smoothing ◽

Product Sales ◽

Exponential Smoothing Method ◽

Single Exponential

PT Tunas Baru Lampung is a company that produces palm cooking oil products under the Rose Brand brand. In product sales, companies sometimes experience ups and downs. Based on the sales data from Rose Brand Cooking Oil, the size of 1 L has fluctuated or in each period it changes and is not always boarding. Even though product sales are one of the important things to be evaluated from time to time on an ongoing basis. To predict future sales, forecasting is done. The forecasting method used is Double Exponential Smoothing and Moving Average. The method of accuracy will be compared using MSE, MAD, and MAPE. The results showed a comparison of the accuracy and the smallest error value in each method. By using the weight values 0.1, 0.3, 0.4, 0.5, 0.6, 0.7, and 0.8 on the Single Exponential Smoothing method the weight value is 0.8 or α = 0.8, namely MSE of 250,570,764.80, MAD of 12,922.32 and MAPE of 33.55 Then, using the movement value n = 3 in the Moving Average method has an accuracy of 438,980,942.75 MSE, 18,142.14 MAD, and 41.37 MAPE. After comparing the accuracy of the two methods, the Single Exponential Smoothing method is the best method to predict sales of Rose Brand 1 L Cooking Oil products.

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Comparison of exponential smoothing method and autoregressive integrated moving average (ARIMA) method in predicting dengue fever cases in the city of Palembang

Journal of Physics Conference Series ◽

10.1088/1742-6596/1521/3/032100 ◽

2020 ◽

Vol 1521 ◽

pp. 032100

Author(s):

E Munarsih ◽

I Saluza

Keyword(s):

Dengue Fever ◽

Moving Average ◽

Exponential Smoothing ◽

Smoothing Method ◽

Autoregressive Integrated Moving Average ◽

Exponential Smoothing Method ◽

The City

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PENERAPAN METODE EXPONENTIAL SMOOTHING UNTUK PERAMALAN JUMLAH KLAIM DI BPJS KESEHATAN PAMEKASAN

Jurnal Matematika MANTIK ◽

10.15642/mantik.2016.2.1.46-51 ◽

2016 ◽

Vol 2 (1) ◽

pp. 46 ◽

Cited By ~ 1

Author(s):

Faisol Faisol ◽

Sitti Aisah

Keyword(s):

Time Series ◽

Average Method ◽

Moving Average ◽

Exponential Smoothing ◽

Time Series Model ◽

Smoothing Method ◽

Repair Procedure ◽

Double Exponential Smoothing ◽

Using Data ◽

Exponential Smoothing Method

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 results with RMSE and MAPE. Based on the research methodology, the result for the period 25 = 833.828, the 26 = 800.256, period 27 = 766.684, a period of 28 = 733.113, period 29 = 699.541, and the period of 30 = 655, 970. Value for RMSE = 98.865 and MAPE = 7.002, In this case the moving average method is also used to compare the results of forecasting with double exponential smoothing method. Forecasting results for the period 25 = 899.208, the 26 = 885, 792, 27 = 872.375 period, a period of 28 = 858.958, period 29 = 845.542, and the period of 30 = 832.125. Value for RMSE = 101.131 and MAPE = 7.756. Both methods together - both have very good performance because the value of MAPE is below 10%, but the method of exponential smoothing has a value of RMSE and MAPE are smaller than the moving average method.

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Solar Irradiance and Load Demand Forecasting based on Single Exponential Smoothing Method

International Journal of Engineering and Technology ◽

10.7763/ijet.2012.v4.408 ◽

2012 ◽

Vol 4 (4) ◽

pp. 451-455 ◽

Cited By ~ 2

Author(s):

P. Y. Lim ◽

C. V. Nayar

Keyword(s):

Solar Irradiance ◽

Demand Forecasting ◽

Exponential Smoothing ◽

Smoothing Method ◽

Load Demand ◽

Exponential Smoothing Method ◽

Single Exponential

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ANALISA PERAMALAN WINTER’S EXPONENTIAL SMOOTHING BROWN DIBANDINGKAN DENGAN AUTOREGRESSIVE INTEGRATED MOVING AVERAGE PADA DATA JUMLAH KEJADIAN HIPERTENSI

Jurnal Ilmu Kesehatan ◽

10.24929/jik.v4i1.695 ◽

2019 ◽

Vol 4 (1) ◽

pp. 1-10

Author(s):

Wisoedhanie Widi .A ◽

Nanik Dwi A.

Keyword(s):

Community Health Centers ◽

Moving Average ◽

Secondary Data ◽

Exponential Smoothing ◽

Smoothing Method ◽

Preventive Action ◽

Autoregressive Integrated Moving Average ◽

Planning And Control ◽

Exponential Smoothing Method ◽

And Control

In an attempt to see and examine the situation and conditions that occur in the future to do forecasting (forecasting). Hypertension is a major disease in the ten Clinics Together and almost every month new hypertension cases occur, so the incidence of hypertension is becoming the trend and forecasting needs to be done. The purpose of this research is to do forecasting on the data the number of incident hypertension in Clinics With the city of Malang with Exponential Smoothing method using winter's Brown compared to Autoregressive Integrated Moving Arima. This type of research is the study of non reactive (non reactive research) which is a type of secondary data for research.Unit samples in this research are patients who come for the medication and patients in Clinics With hypertension Malang. in 2013 to 2016. Research data using Minitab software. The results of this study showed that both methods of forecasting results shows that tend to decrease in the year 2018 with the lowest incidence in December that as many as 58 incidents on Exponential Smoothing method of winter's and some 80 events on the method of Autoregressive Integrated Moving Average. The existence of a trend of decrease in the incidence of hypertension can be supported by the growing health services at community health centers With has been doing various efforts in preventive action, promotif and collaborative in the handling of problems Hypertension.Through these research results, it is advisable to draw up a health center party planning and control and eradication programs work for transmission of diseases of hypertension (P2P) with reference to the results of the forecasting incidence of hypertension in the year 2018.

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Patient Visit Forecasting at Emergency Department using Autoregressive Integrated Moving Average (ARIMA) and Exponential Smoothing Method in RSUD Kembangan

Proceedings of the 1st International Conference on Health ◽

10.5220/0009590302340239 ◽

2019 ◽

Author(s):

Nurul Baharsyah ◽

Mieke Nurmalasari

Keyword(s):

Emergency Department ◽

Moving Average ◽

Exponential Smoothing ◽

Smoothing Method ◽

Patient Visit ◽

Autoregressive Integrated Moving Average ◽

Exponential Smoothing Method

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Analisis Peramalan (Forecasting) Penjualan Jasa Pada Warnet Bulian City di Muara Bulian

Eksis: Jurnal Ilmiah Ekonomi dan Bisnis ◽

10.33087/eksis.v10i1.160 ◽

2019 ◽

Vol 10 (1) ◽

pp. 61

Author(s):

Fauziah Fauziah ◽

Yulia Istia Ningsih ◽

Eva Setiarini

Keyword(s):

Error Rate ◽

Average Method ◽

Forecast Error ◽

Moving Average ◽

Exponential Smoothing ◽

Smoothing Method ◽

Business World ◽

Business Forecasting ◽

Double Exponential Smoothing ◽

Exponential Smoothing Method

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 rate Forecasting using the MA (Moving Average) method for 3 periods is predicted the level of profit to be gained by Bulian City Warnet in August amounted to. 11,117,833 with MAD 1,487,370. Forecasting using the Weigh Moving Averages (WMA) 3 method is forecasted at 12,287,300 with MAD Error 3,016,016 while the forecast using the double exponential smoothing method is 13,522,572 with MAD 5513617,364 then the forecasting method chosen is the Single Exponential Smoothing method with the Forecast value in August 2018 9,581.69 for the The Forecast Error is MAD of 1,378,375 which is the method with the smallest error rate.

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