Prediksi stok barang di PT. Satria Jaya Prima menggunakan algoritma SES
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Institusion
Universitas Katolik Musi Charitas
Author
Valiandri, Antika
Subject
TN Mining engineering. Metallurgy
Datestamp
2022-03-07 08:50:38
Abstract :
A problem requires a solution to solve it. One of them is by using Prediction. PT. Satria Jaya Prima, when going to order goods to the center does not have definite information about the stock of goods available in the warehouse. Therefore, we need a tool in the form of software that can help facilitate and maximize the performance of company employees in predicting the number of items that must be ordered to the center for the following month. The data used in this research is historical data in the form of Dynamix Cement, Semen Padang, Power Max Cement, Tecking Tires and Fosroc Waterproof Paint in the last 100 months. Single Exponential Smoothing is a method that continuously improves forecasting by taking the past average value of smoothing (smoothing) from a time series data in a decreasing way (exponential). In this study, an evaluation of the prediction results with MAPE (mean absolute percentage error) will be carried out. The smallest error value or the one with the lowest error is obtained when using the Single Exponential Smoothing (SES) method with an alpha value of 0.1-0.9, the difference between the alpha values used is influenced by the different amounts of each item. The programming language used is the PHP programming language, using MySQL in processing the database. The results of this study were obtained on Semen Padang with an alpha of 0.2-0.3 with an MAPE value of 15%, Semen Power Max with an alpha of 0.7-0 .9 MAPE 22%, Semen Dynamix with an alpha of 0.8-0.9 with a MAPE value of 21%, Tecking Tires with an alpha of 0.5-0.9 MAPE values of 24% and Fosroc Waterproof Paint with an alpha of 0.8-0.9 MAPE values of 24%. Keywords: Stock prediction, Single Exponential Smoothing (SES), PHP, MySQL
A problem requires a solution to solve it. One of them is by using Prediction. PT. Satria Jaya Prima, when going to order goods to the center does not have definite information about the stock of goods available in the warehouse. Therefore, we need a tool in the form of software that can help facilitate and maximize the performance of company employees in predicting the number of items that must be ordered to the center for the following month. The data used in this research is historical data in the form of Dynamix Cement, Semen Padang, Power Max Cement, Tecking Tires and Fosroc Waterproof Paint in the last 100 months. Single Exponential Smoothing is a method that continuously improves forecasting by taking the past average value of smoothing (smoothing) from a time series data in a decreasing way (exponential). In this study, an evaluation of the prediction results with MAPE (mean absolute percentage error) will be carried out. The smallest error value or the one with the lowest error is obtained when using the Single Exponential Smoothing (SES) method with an alpha value of 0.1-0.9, the difference between the alpha values used is influenced by the different amounts of each item. The programming language used is the PHP programming language, using MySQL in processing the database. The results of this study were obtained on Semen Padang with an alpha of 0.2-0.3 with an MAPE value of 15%, Semen Power Max with an alpha of 0.7-0 .9 MAPE 22%, Semen Dynamix with an alpha of 0.8-0.9 with a MAPE value of 21%, Tecking Tires with an alpha of 0.5-0.9 MAPE values of 24% and Fosroc Waterproof Paint with an alpha of 0.8-0.9 MAPE values of 24%. Keywords: Stock prediction, Single Exponential Smoothing (SES), PHP, MySQL
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IF-2021-1713008-cover.pdf
IF-2021-1713008-abstract.pdf
IF-2021-1713008-complete.pdf
IF-2021-1713008-summary_id.pdf
IF-2021-1713008-tableofcontent.pdf
IF-2021-1713008-chapter1.pdf
IF-2021-1713008-chapter2.pdf
IF-2021-1713008-chapter3.pdf
IF-2021-1713008-chapter4.pdf
IF-2021-1713008-conclusion.pdf
IF-2021-1713008-reference.pdf
IF-2021-1713008-attachment.pdf
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