ANALSIS PERAMALAN PENJUALAN TEPUNG TAPIOKA DI CV. XYZ LAMPUNG

Abstract

This research was motivated by the uncertainty in the sales of tapioca flour which weakened the tapioca industry of CV. XYZ. This makes the company less able to optimize the company's capital and profits. The purpose of this study was to analyze the most suitable sales forecasting method for tapioca flour CV. XYZ. It is very important to forecast sales using POM QM version 5.2 software. Sales forecasting analysis (forecasting) uses five methods, namely Linear Regression, Moving Average, Weighted Moving Average, Exponential Smoothing, and exponential smoothing with trends using tapioca flour sales data for the last 5 (five) years. The results of the analysis show that the Linear Regression method is a suitable forecasting method used in the industrial sales of tapioca CV. XYZ with MAD, MSE, and MAPE values compared to other methods, namely 3424.9, 14,948,800, and 13.43%, with forecast results in 2020 of 21,800 tons of tapioca flour.