scholarly journals Sistem Informasi Pengendali Persediaan Barang Menggunakan Metode Triple Exponential Smoothing untuk Peramalan Penjualan (Studi Kasus : Luna Pet Shop)

Jurnal INFORM ◽  
2016 ◽  
Vol 1 (2) ◽  
Author(s):  
Edi Mardiansyah ◽  
Dwi Cahyono ◽  
Ratna Nur Tiara Shanty
Keyword(s):  
Information System ◽  
Inventory Control ◽  
Computer Technology ◽  
Exponential Smoothing ◽  
Statistical Information ◽  
Smoothing Method ◽  
Sales Data ◽  
Control Information ◽  
Inventory Constraints ◽  
Exponential Smoothing Method

Abstract - Advances in computer technology is growing very fast and has an important role as a center of data and informationsystems to assist the transactional Luna Petshop and controlling inventory. Constraints of Luna Petshop that can not determine the amount of sales of goods in the next period, resulting in inhibition of the sales transaction for out of stock items. Inventory control information system uses Triple Exponential Smoothing method is the solution to forecast sales and provide recommendations on supplier purchases in the months ahead by analyzing historical sales data for previous periods. This information system also may provide statistical information regarding the sale and purchase of every month, if the sale or purchase of an increase or decrease

scholarly journals GOOD SALES FORECASTING INFORMATION SYSTEM USING SINGLE EXPONENTIAL SMOOTHING METHOD

2021 ◽  
Vol 14 (1) ◽  
pp. 77-82
Author(s):  
Rahmadini Darwas ◽  
Rahimullaily Rahimullaily ◽  
Naufal Abdi
Keyword(s):  
Information System ◽  
Exponential Smoothing ◽  
Mean Value ◽  
Smoothing Method ◽  
Sales Data ◽  
Cooking Oil ◽  
The Mean ◽  
Exponential Smoothing Method ◽  
Single Exponential

This study aims to determine the estimated number of items sold at one of the mini market, namely the Tita shop, especially Sari Murni cooking oil, 2 liter packs for the next one month based on sales data for January 2016 to December 2017. The problems that occur at Tita`s shop are is difficult to estimate the amount of stock of goods and calculate the estimated cost required for sales in the next month period, so it is necessary to build a forecasting information system using the single exponential smoothing method which assumes that the data fluctuates around the mean value without any trend or seasonal elements. This study resulted in the amount of 2 liter packaged sari murni cooking oil in Januari 2018, which was 42 pcs. Meanwhile, the estimated cost required to buy 2 liter packaged cooking oil stock in that period is Rp. 609.000,00 with a capital price unit of goods Rp. 14.500,00.

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 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.

scholarly journals TRIPLE EXPONENTIAL SMOOTHING: FORECASTING PERBANDINGAN PENUMPANG KERETA API DAN PESAWAT TERBANG

2020 ◽  
Vol 18 (2) ◽  
pp. 277
Author(s):  
Khoirin Azaro ◽  
Nur Indah Riwajanti ◽  
Anik Kusmintarti
Keyword(s):  
Consumer Demand ◽  
Exponential Smoothing ◽  
Smoothing Method ◽  
Seasonal Patterns ◽  
Efficient Planning ◽  
Exponential Method ◽  
Exponential Smoothing Method ◽  
Airline Company

This research aims to predict the number of train and airplane passengers in 2020. Forecasting of train and airplane passengers is interest to analyze and estimate consumer demand to help the train or airline company prepare effective and efficient planning. This type of research is descriptive quantitative and uses data taken from the Indonesian Statistic Agency (BPS). Data were analyzed using Exponential smoothing Method. Train and airplane passenger data shows trend and seasonal patterns so that the exponential method used is Triple Exponential smoothing. The results of the study show that train passengers in 2020 are increase. While forecast results related to aircraft passengers in 2020 also tend to increase.

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