Analisis Peramalan Penjualan Getuk Goreng Sokaraja Menggunakan Metode Moving Average, Weighted Moving Average, Dan Exponential Smoothing (Studi Kasus : Getuk Goreng Sari Dewi)

Jeni, Merlina (2023) Analisis Peramalan Penjualan Getuk Goreng Sokaraja Menggunakan Metode Moving Average, Weighted Moving Average, Dan Exponential Smoothing (Studi Kasus : Getuk Goreng Sari Dewi). Undergraduate Thesis thesis, Institut Teknologi Telkom Purwokerto.

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Abstract

MSMEs are one of the fields that make a significant contribution to helping economic growth in Indonesia. According to Kuncoro (2009) said that there are 4 advantages of MSMEs so that they can survive the economic crisis, namely not using foreign loans, not having too large debts in banks, the input process almost all use local Indonesian products, a fairly good and promising export orientation base. Getuk Goreng Sari Dewi is an example of MSMEs in Sokaraja which is quite well known, during the pandemic the sales of fried getuk decreased greatly, even at the beginning of the pandemic turnover decreased by 50%, sales in this home industry could not be predicted because all existing activities were still carried out manually. This makes all activities ineffective because it takes a lot of time and energy both for the production, ordering and selling of products. Therefore, research related to sales forecasting is needed as a solution to these problems. Forecasting is the most appropriate solution for every company or business person to make decisions. Forcasting in this study will use the Time Series method. The method will be calculated using Moving Average, Weighted Moving Average, and Exponential Smoothing. The existence of this sales forecasting is expected to help owner. Home Industry Getuk Goreng Sari Dewi to forecast the number of prodak sales to match the production amount based on the calculation of the Time Series method and to provide recommendations regarding the amount of production that must be carried out in accordance with market demand. Based on the application of this method in the home industry Getuk Goreng Sari Dewi, sales forecasting in February, March, and April was obtained by 16,600 Moving Average forecasting in February, 16,800 Moving Average forecasting in March, 16,333 Moving Average forecasting in April, 16,300 Weighted Moving Average forecasts in February, 17,083 Weighted Moving Average forecasts in March,16,083 Weighted Moving Average forecasts in April, 16,543 Exponential Smoothing forecasts in February, 16,414 Exponential Smoothing forecasts in March, and 16,478 Exponential Smoothing forecasts in April. Keywords: Home industry, Forecasting, Supply Chain, Time Series, MSMEs

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