Implementation of Trend Moment Method in Gasoline Stock Forecasting (Case Study : SPBU Rest Area 25 - Sidoarjo)

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Published: Jan 11, 2024
Keywords:
Trend Moment, Forecasting, Predictions

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Agung Muliawan
Institut Teknologi dan Sains Mandala
Iqbal Sabilirrasyad
Institut Teknologi dan Sains Mandala
Mas’ud Hermansyah
Institut Teknologi dan Sains Mandala
Difari Afreyna Fauziah
Institut Teknologi dan Sains Mandala
Faiz Firdausi
Institut Teknologi dan Sains Mandala

Abstract

Sales Forecasting is the activity of estimating products to be sold at a future time under certain circumstances and is made based on data that has occurred and or is unlikely to occur. One of the forecasts needed is gasoline stock forecasting carried out at Rest Area 25 Gas Station - Sidoarjo. The purpose of this study is to determine how fuel sales forecasting with the use of the Trend Moment Method in the Rest Area 25 - Sidoarjo gas station case study can help predict uncertain fuel demand. Data collection techniques used observation, documentation and literature study methods and data analysis techniques are quantitative data. The data used in this study is gasoline sales data in 2017-2018. Implementation of the program using the VB programming language. NET programming language and SQL Server. The results of this study obtained an average error value using APE of 18.63% with an accuracy of 81.36% which is good value

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How to Cite
Muliawan, A., Sabilirrasyad, I., Hermansyah, M., Afreyna Fauziah, D., & Firdausi, F. (2024). Implementation of Trend Moment Method in Gasoline Stock Forecasting (Case Study : SPBU Rest Area 25 - Sidoarjo). LOREM: Computational Engineering and Computer Information Systems, 1(1), | Page 27 - 35. https://ejournal.mediakunkun.com/index.php/lorem/article/view/23
Issue
Vol. 1 No. 1 (2024): January - April 2024
Section
Articles

How to Cite

Muliawan, A., Sabilirrasyad, I., Hermansyah, M., Afreyna Fauziah, D., & Firdausi, F. (2024). Implementation of Trend Moment Method in Gasoline Stock Forecasting (Case Study : SPBU Rest Area 25 - Sidoarjo). LOREM: Computational Engineering and Computer Information Systems, 1(1), | Page 27 - 35. https://ejournal.mediakunkun.com/index.php/lorem/article/view/23

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