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

2020 ◽  
Vol 1521 ◽  
pp. 032100
Author(s):  
E Munarsih ◽  
I Saluza
2019 ◽  
Vol 4 (1) ◽  
pp. 1-10
Author(s):  
Wisoedhanie Widi .A ◽  
Nanik Dwi A.

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.


2021 ◽  
Vol 1 (1) ◽  
pp. 15-20
Author(s):  
Novianti Novianti ◽  
Muhammad Amin ◽  
Wan Mariatul Kifti

Abstract : This study aims to determine thecrime rate in motorbike theft cases using the programmeing langiage PHP and MySQL as a database and the application of the Exponential Smoothing method to determine the crime rate of motorcycle theft that occurs in the city of Tanjung Balai for the next period. The data used in this study is motorcycle theft report data from 2018 to 2019 wich was obtained from the Tanjung Balai Police. The benefits of this research can be used by the Tanjung Balai police to determine the extent of the motorcycle theft crime that will occur in a shorter, easier and more accurate manner so that it can take optimal prevention. With the Exponential Smoothing method the alpha value will be searched randomly to find an alpha value that was a minimum error value calculated using Means Absolute Percetage Error (MAPE). Then the prediction results that have an alphan with a minimum error are the best of recommended as a prediction result for the next period. Based on this research, the prediction results obtained from the prediction of the number of motorcycle theft cases the occurred in the city of Tanjung Balai in 2020 were 12 units with an MAPE error value of 0,153%. Keyword : Exponential Smoothing, Theft, Motorcycle, Forecasting  Abstrak : Penelitian ini bertujuan untuk menentukan tingkat kriminalitas kasus pencurian sepeda motor dengan menggunakan bahasa pemrograman PHP dan MySQL sebagai basis data serta penerapan metode Exponential Smoothing untuk menentukan tingkat kriminalitas pencurian sepeda motor yang terjadi di kota Tanjung Balai untuk periode berikutnya. Data yang digunakan dalam penelitian ini adalah data laporan pencurian sepeda motor dari tahun 2018 sampai dengan tahun 2019 yang diperoleh dari POLRES Tanjung Balai. Manfaat dari penelitian ini dapat digunakan oleh kepolisian Tanjung Balai untuk menentukan seberapa besar tindak kriminalitas pencurian sepeda motor yang akan terjadi secara lebih singkat, mudah dan akurat sehingga dapat melakukan pencegahan yang optimal. Dengan metode Exponential Smoothing  akan dicari nilai alpha secara acak sampai menemukan nilai alpha yang memiliki nilai error yang minimum yang dihitung menggunakan Means Absolute Percetage Error (MAPE). Maka hasil prediksi yang memiliki alpha dengan error minimumlah yang paling baik atau direkomendasikan sebagai hasil prediksi untuk periode selanjutnya. Berdasarkan penelitian ini diperoleh hasil prediksi peramalan jumlah kasus pencurian sepeda motor yang terjadi di kota Tanjung Balai tahun 2020 adalah 12 unit dengan nilai error MAPE sebesar 0,153%. Kata Kunci : Exponential Smoothing, Pencurian, Sepeda Motor, Forecasting


JUDICIOUS ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 134-137
Author(s):  
Siti Juriah

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.


2021 ◽  
Vol 6 (2) ◽  
pp. 101
Author(s):  
Niken Chaerunnisa ◽  
Ade Momon

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.


2016 ◽  
Vol 2 (1) ◽  
pp. 46 ◽  
Author(s):  
Faisol Faisol ◽  
Sitti Aisah

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.


2019 ◽  
Vol 10 (1) ◽  
pp. 61
Author(s):  
Fauziah Fauziah ◽  
Yulia Istia Ningsih ◽  
Eva Setiarini

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.


2013 ◽  
Vol 13 (1) ◽  
pp. 68
Author(s):  
Romy Biri ◽  
Yohanes A.R Langi ◽  
Marline S Paendong

PENGGUNAAN METODE SMOOTHING EKSPONENSIAL DALAM MERAMAL PERGERAKAN INFLASI KOTA PALU ABSTRAK Penelitian dilakukan untuk mengetahui pergerakan inflasi dan meramal pergerakan inflasi di Kota Palu. Data pergerakan inflasi ini berjumlah 160 data bulan pengamatan, dari januari 2000 sampai april 2013. Peramalan pergerakan inflasi di Kota Palu sebesar 0,2683 persen, artinya pergerakan inflasi di Kota Palu kembali mengalami penurunan dari periode bulan sebelumnya. Data peramalan pergerakan ini, tidak mengalami perbedaan yang signifikan di bandingkan dengan data yang di keluarkan oleh Badan Pusat Statistika di kota tersebut. Kata kunci : Meramal Pergerakan Inflasi, Smoothing Eksponential tunggal THE USING OF EXPONENTIAL SMOOTHING METHOD TO PREDICT INFLATION MOVEMENT FROM PALU CITY ABSTRACT The Research was conducted to determine the movement of inflation and predicting it in Palu. The data of inflation movement numbered 160 data observation month, from January 2000 until April 2013. Predicting the movement of inflation in Palu of 0,2683 percent, it means the movement of inflation in Palu decreased again from month period previously. The data of these movement, not significant difference in comporison with the data that released by Central Statistical Corporation in the city. Keywords : Predicting the Movement of Inflation, Single Exponential Smoothing


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