SISTEM INFORMASI PENGELOLAAN STOK BARANG DENGAN MENGGUNAKAN METODE SINGLE EXPONENTIAL SMOOTHING

Estimating sales quantity is an activity to estimate the amount of product sales by producers or distributors in a certain period of time and marketing area. Prediction of sales quantity is part of the management function as one of the contributors to the success of a company. Prediction of the quantity of product sales in the future is intended to control the number of existing product stocks, so that shortages or excess stock of products can be minimized. CV Kabul Jaya in managing stock of goods has problems, the problem is that the estimated shopping or stock of goods in the next period or the period of the following month does not match the reality or the actual demand for goods. This problem disrupts the company's financial cycle and can even suffer losses. The Single Exponential Smoothing method is a method used to estimate the number of goods in the future. This method is often used and has been proven to be able to estimate the amount of inventory in the future. In this study, the author makes a stock forecast information system at CV.Kabul Jaya using this method. The results of this study on one type of item using this method produce an estimate of goods in the period of the twelfth month at the smallest Mean Squared Error (MSE) value, namely at α 0.5 with an MSE value of 18.82 the resulting estimate for the item 58. This system has been created and has been tested for its validity and the result is that this system is suitable for use in estimating stock items.

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Publication Details

Journal
Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN)
Published
2024-12-30
DOI
https://doi.org/10.30646/tikomsin.v12i2.874
Primary Topic
Management and Optimization Techniques
Type
article
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article

SISTEM INFORMASI PENGELOLAAN STOK BARANG DENGAN MENGGUNAKAN METODE SINGLE EXPONENTIAL SMOOTHING

Retno Tri Vulandari, Hendro Wijayanto, Zulkifly Setyo Nugroho
Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN)
Management and Optimization Techniques
article

SISTEM INFORMASI PENGELOLAAN STOK BARANG DENGAN MENGGUNAKAN METODE SINGLE EXPONENTIAL SMOOTHING

Retno Tri Vulandari, Hendro Wijayanto, Zulkifly Setyo Nugroho
article en

Abstract

Estimating sales quantity is an activity to estimate the amount of product sales by producers or distributors in a certain period of time and marketing area. Prediction of sales quantity is part of the management function as one of the contributors to the success of a company. Prediction of the quantity of product sales in the future is intended to control the number of existing product stocks, so that shortages or excess stock of products can be minimized. CV Kabul Jaya in managing stock of goods has problems, the problem is that the estimated shopping or stock of goods in the next period or the period of the following month does not match the reality or the actual demand for goods. This problem disrupts the company's financial cycle and can even suffer losses. The Single Exponential Smoothing method is a method used to estimate the number of goods in the future. This method is often used and has been proven to be able to estimate the amount of inventory in the future. In this study, the author makes a stock forecast information system at CV.Kabul Jaya using this method. The results of this study on one type of item using this method produce an estimate of goods in the period of the twelfth month at the smallest Mean Squared Error (MSE) value, namely at α 0.5 with an MSE value of 18.82 the resulting estimate for the item 58. This system has been created and has been tested for its validity and the result is that this system is suitable for use in estimating stock items.

Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN)Vol. 12(2)
Openalex Percentile: Top 51%
Management and Optimization Techniques
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SISTEM INFORMASI PENGELOLAAN STOK BARANG DENGAN MENGGUNAKAN METODE SINGLE EXPONENTIAL SMOOTHING — Retno Tri Vulandari, Hendro Wijayanto, et al. · Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN) (2024) | TGRS Research Map | TGRS