Requirement Forecasting of Equipment’s Maintenance Spares-Parts Based on Exponential Smoothing Method

2012 ◽  
Vol 605-607 ◽  
pp. 9-13
Author(s):  
Xiao Chun Liu ◽  
Yong Liang Zhang ◽  
Ai Jun Huang ◽  
Li Ya Xu
Keyword(s):  
Exponential Smoothing ◽  
Smoothing Method ◽  
Forecasting Model ◽  
Microsoft Excel ◽  
Alternative Approach ◽  
Forecasting Method ◽  
Exponential Smoothing Method

Management of equipment’s maintenance spares-parts is one of important contents of equipment support. In allusion to the problem of requirement forecasting of maintenance equipment spares-parts, and based on exponential smoothing method, a requirement forecasting model of equipment’s maintenance spares-parts was built. Microsoft EXCEL was employed to forecast the equipment’s maintenance spares-parts requirements. The forecasting method provides a scientific and alternative approach to forecast requirement of equipment’s maintenance equipment.

scholarly journals Forecasting Shoe Sales Volume with Exponential Smoothing Method at PT Kujang Utama Antasena - Bogor

JUDICIOUS ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 134-137
Author(s):  
Siti Juriah
Keyword(s):  
Moving Average ◽  
Control Process ◽  
Exponential Smoothing ◽  
Smoothing Method ◽  
Smoothing Factor ◽  
Planning And Control ◽  
Shoe Industry ◽  
Forecasting Method ◽  
Exponential Smoothing Method ◽  
And Control

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.

scholarly journals IMPLEMENTASI METODE EXPONENTIAL SMOOTHING UNTUK PERAMALAN KEDATANGAN WISATAWAN MANCANEGARA PADA PULAU BALI

2020 ◽  
Vol 18 (2) ◽  
pp. 171
Author(s):  
Nafis Sulthan ◽  
Nurafni Eltivia ◽  
Nur Indah Riwajanti
Keyword(s):  
Decision Making ◽  
Error Rate ◽  
Exponential Smoothing ◽  
Smoothing Method ◽  
Seasonal Patterns ◽  
Microsoft Excel ◽  
Foreign Tourist ◽  
Tourism Sector ◽  
Quantitative Descriptive ◽  
Exponential Smoothing Method

The purpose of this study is to predict the arrival of foreign tourists on the island of Bali by using the Exponential Smoothing method. This research is a quantitative descriptive. The data used in the study are data on foreign tourist arrivals from the air and sea routes taken from the Central Statistics Agency. Data is managed through the Microsoft Excel application. In determining the RMSE, the Solver Parameters help listed in Microsoft Excel is used to determine the lowest error rate. The data used in this study indicate that there are trend and seasonal patterns so that the most suitable Exponential Smoothing method is the Triple Exponential Smoothing method. The results of this study indicate that foreign tourist arrivals on the island of Bali are predicted to increase in 2020 although not too significant. The results of this study are expected to help the Bali Island government and related agencies in terms of planning and decision making to overcome the crisis on the island of Bali caused by the tourism sector.

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

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.

scholarly journals FORECASTING USES DOUBLE EXPONENTIAL SMOOTHING METHOD AND FORECASTING VERIFICATION USES TRACKING SIGNAL CONTROL CHART (CASE STUDY: IHK DATA OF EAST KALIMANTAN PROVINCE)

2020 ◽  
Vol 14 (1) ◽  
pp. 013-022
Author(s):  
Humairo Dyah Puji Habsari ◽  
Ika Purnamasari ◽  
Desi Yuniarti
Keyword(s):  
Control Chart ◽  
Exponential Smoothing ◽  
Smoothing Method ◽  
Signal Control ◽  
East Kalimantan ◽  
Forecasting Method ◽  
Double Exponential ◽  
Double Exponential Smoothing ◽  
Exponential Smoothing Method ◽  
Tracking Signal

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 metode peramalan double exponential smoothing berdasarkan nilai MAPE terkecil, memperoleh hasil verifikasi metode peramalan double exponential smoothing terbaik berdasarkan grafik pengendali tracking signal, dan memperoleh hasil peramalan menggunakan metode double exponential smoothing terbaik. Hasil penelitian menunjukkan metode peramalan terbaik adalah metode double exponential smoothing dari Holt dengan parameter  dan berdasarkan nilai MAPE terkecil sebesar 0,361% dan nilai tracking signal yang keseluruhan terkendali pada grafik pengendali tracking signal.   Kata kunci: Double Exponential Smoothing, IHK, MAPE, Tracking signal.   Abstract Forecasting is a technique for estimating a value in the future by looking at past and current data. Data that shows a trend, matches the Brown’s  exponential smoothing forecasting method or Holt's double exponential smoothing method. Forecasting of double exponential smoothing method in this study was applied to the IHK data of East Kalimantan Province for the period of January 2016 to February of 2019 which has a trend pattern. The purpose of this study was to obtain the results of the accuracy comparison of the double exponential smoothing forecasting method based on the smallest MAPE value, obtain the best verification results of the double exponential smoothing forecasting method based on tracking signal control charts, and obtain the best forecasting results using the double exponential smoothing method. The results showed that the best forecasting method was Holt's double exponential smoothing method with parameters  and based on the smallest MAPE value of 0.361% and the overall tracking signal value was controlled on the tracking signal control chart.  Keywords: Double Exponential Smoothing , IHK, MAPE, Tracking signal.  

scholarly journals Forecasting The Amount of Tuna/Madidihang (Yellowfin tuna) Landed in PPS Kutaraja Banda Aceh City With The Triple Exponential Smoothing Method

2019 ◽  
Vol 10 (1) ◽  
pp. 08-14
Author(s):  
Muhammad Haikal Nasution ◽  
Samsul Anwar ◽  
Aida Fitri ◽  
Aja Fatimah Zohra
Keyword(s):  
International Markets ◽  
Exponential Smoothing ◽  
Yellowfin Tuna ◽  
Smoothing Method ◽  
Local Market ◽  
Monthly Data ◽  
Forecasting Method ◽  
Aceh Province ◽  
Exponential Smoothing Method ◽  
Banda Aceh

The Kutaraja Ocean Fisheries Port (PPS) located in Banda Aceh City is central to the fisheries sector in Aceh Province. Various types of fish have been landed at Kutaraja PPS, one of which is tuna/madidihang (yellowfin tuna). Tuna is not only in demand by the local market, but also international markets, especially Japan and America. This study aims to estimate the amount of tuna/madidihang (yellowfin tuna) production landed at Kutaraja PPS in 2018 and 2019. These estimates can help the Aceh Government in controlling the ordering of tuna/madidihang (yellowfin tuna) from within and outside the country, so that the number of tuna/madidihang (yellowfin tuna) caught and ordered can be balanced so that stock control can run well. The forecasting method used in this study is the Triple Exponential Smoothing method by using monthly data on the amount of tuna/madidihang (yellowfin tuna) production landed at Kutaraja PPS from January 2010 to December 2017. Based on the results of forecasting with the best models, the amount of tuna/madidihang (yellowfin tuna) production will landed in the Kutaraja PPS in 2018 and 2019 are predicted to be 2,395,615.8 Kg and 2,451,207.5 Kg respectively.

scholarly journals ANALISIS FORECASTING DEMAND DENGAN METODE LINEAR EXPONENTIAL SMOOTHING (STUDI PADA: PRODUK BATIK FENDY, KLATEN)

2020 ◽  
Vol 16 (2) ◽  
pp. 81-89
Author(s):  
Nita Kusuma Wardani ◽  
Muhammad Roestam Afandi ◽  
Lilia Pasca Riani
Keyword(s):  
Secondary Data ◽  
Descriptive Study ◽  
Exponential Smoothing ◽  
Smoothing Method ◽  
Production Data ◽  
Sales Data ◽  
Forecasting Methods ◽  
Forecasting Method ◽  
Quantitative Descriptive ◽  
Exponential Smoothing Method

Abstrak: Tujuan dari penelitian ini adalah untuk mengevaluasi tingkat akurasi peramalan permintaan Batik Fendy menggunakan teknik MAPE. Adapun jenis penelitian ini merupakan penelitian deskriptif kuantitatif, menggunakan data sekunder dari penjualan perusahaan Batik Fendy periode bulan November 2018 - Onkoter 2019. Terdapat 5 tahapan dalam analisis data, yaitu 1) mentabulasikan data penjualan dan data produksi batik Fendy, 2) mengevaluasi metode peramalan penjualan yang dilakukan oleh perusahaan Batik Fendy dengan teknik MAPE, 3) memproyeksikan nilai alpha dan beta sebagai dasar peramalan linear exponential smoothing, 4) melakukan peramalan permintaan Batik Fendy dengan metode Linear Exponential Smoothing, dan 5) melakukan evaluasi metode peramalan dengan teknik MAPE. Hasil penelitian ini adalah nilai MAPE dari peramalan permintaan yang dilakukan oeh perusahaan Batik Fendy adalah sebesar 17,5%; angka ini menunjukkan tingkat persentase kesalahan paling tinggi pada varian Batik Sarimbit Lengan Panjang, kemudian dengan data penjualan varian ini dilakukan peramalan penjualan dengan metode Linear Exponential Smoothing dan diperoleh MAPE sebesar 9,21%. Sehingga dapat disimpulkan bahwa penggunaan metode Linear Exponential Smoothing dalam memprediksi penjualan Batik Fendy varian Sarimbit Lengan Panjang lebih akurat.Abstract: The purpose of this study was to evaluate the accuracy of forecasting demand for Batik Fendy using MAPE techniques. The type of this research is a quantitative descriptive study, using secondary data from the sales of the company Batik Fendy in the period November 2018 - October 2019. There are five stages in data analysis, namely 1) tabulating sales data and production data of Fendy batik, 2) evaluating sales forecasting methods conducted by the Batik Fendy company with the MAPE technique, 3) projecting alpha and beta values as the basis for forecasting linear, exponential smoothing, 4) forecasting requests for Batik Fendy with the Linear Exponential Smoothing method, and 5) evaluating the forecasting method with the MAPE technique. The results of this study are the MAPE value of demand forecasts made by the Batik Fendy company is 17.5%. This figure shows the highest percentage of error in the variant of the Sarimbit Long Sleeve Batik. With the sales data, this variant is forecasted by using the Linear Exponential Smoothing method and obtained a MAPE of 9.21%. So it can be concluded that the use of the Linear Exponential Smoothing method in predicting sales of the Sarimbit Arm Long Variant Batik is accurate.

scholarly journals PERAMALAN JUMLAH PENUMPANG PESAWAT DI BANDARA INTERNASIONAL AHMAD YANI DENGAN METODE HOLT WINTER’S EXPONENTIAL SMOOTHING DAN METODE EXPONENTIAL EMOOTHING EVENT BASED

2020 ◽  
Vol 9 (4) ◽  
pp. 535-545
Author(s):  
Sofiana Sofiana ◽  
Suparti Suparti ◽  
Arief Rachman Hakim ◽  
Iut Triutami
Keyword(s):  
Historical Data ◽  
Seasonal Pattern ◽  
Exponential Smoothing ◽  
Smoothing Method ◽  
International Airport ◽  
Special Event ◽  
Special Events ◽  
Forecasting Method ◽  
Event Based ◽  
Exponential Smoothing Method

Forecasting the number of airplane passengers can be a consideration for the airline at Ahmad Yani International Airport related with addition of extra flight. The number of airplane passengers can be influenced by certain seasonal or special events. The seasonal influences can be known through historical data patterns and if there is a seasonal pattern, the Holt Winter’s Exponential Smoothing method can be used. Exponential Smoothing Event Based (ESEB) forecasting method can be use to see the special events that effect the number of airplane passengers at Ahmad Yani International Airport. After compared, the Holt Winter’s Exponential Smoothing method is a better method of forecasting the number of airplane passengers at Ahmad Yani International Airport because it has a smaller error value, namely the MSE value and the MAPE value than the Exponential Smoothing Event Based (ESEB)method. The MAPE and MSE values be produced from the best method each of  5,644139% and 619,998,718 .Keywords : Airplane Passengers, Seasonal Pattern, Special Event, Exponential Smoothing Event Based , Holt Winter’s Exponential Smoothing.

scholarly journals The Analysis of Forecasting Demand Method of Linear Exponential Smoothing

2020 ◽  
pp. 7-18
Author(s):  
Nita Kusuma ◽  
Muhammad Roestam ◽  
Lilia Pasca
Keyword(s):  
Secondary Data ◽  
Descriptive Study ◽  
Exponential Smoothing ◽  
Smoothing Method ◽  
Production Data ◽  
Sales Data ◽  
Forecasting Methods ◽  
Forecasting Method ◽  
Quantitative Descriptive ◽  
Exponential Smoothing Method

The purpose of this study was to evaluate the accuracy of forecasting demand for Batik Fendy using MAPE techniques. The type of this research is a quantitative descriptive study, using secondary data from the sales of the company Batik Fendy in the period November 2018 - Onkoter 2019. There are 5 stages in data analysis, namely 1) tabulating sales data and production data of Fendy batik, 2) evaluating sales forecasting methods conducted by the Batik Fendy company with the MAPE technique, 3) projecting alpha and beta values ​​as the basis for forecasting linear exponential smoothing , 4) forecasting requests for Batik Fendy with the Linear Exponential Smoothing method , and 5) evaluating the forecasting method with the MAPE technique. The results of this study are the MAPE value of demand forecasts made by the Batik Fendy company is 17.5%; This figure shows the highest percentage of error in the variant of the Sarimbit Long Sleeve Batik, then with the sales data this variant is forecasted by using the Linear Exponential Smoothing method and obtained a MAPE of 9.21%. So it can be concluded that the use of the Linear Exponential Smoothing method in predicting sales of the Sarimbit Arm Long variant Batik is more accurate.

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