Peramalan Permintaan Minyak Goreng untuk Perencanaan Kebutuhan Crude Palm Oil di PT. PQS

PQS is a company engaged in the processing of Crude Palm Oil (CPO). The production system employed is make-to-stock, with production planning based on estimates and without the implementation of any specific method for production forecasting. Consequently, this has led to unmet consumer demand, with consumers having to wait until the cooking oil is available and distributed (out of stock). The objective of this research is to forecast the demand for cooking oil to plan for CPO needs and to determine the forecasted results for five periods, spanning from August to December 2023. The methods employed include Single Moving Average and Single Exponential Smoothing, validated by the POM-QM application. Based on the calculation results using the Single Moving Average method, an MAPE (Mean Absolute Percentage Error) of 13.12% was obtained, while the Single Exponential Smoothing method resulted in an MAPE of 14.44%. The chosen method for obtaining the most accurate forecasting method for cooking oil demand for CPO needs is the Single Moving Average method, as it has a smaller error rate. Keywords: Forecasting, Single Moving Average, Single Exponential Smoothing

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Publication Details

Journal
Industrika Jurnal Ilmiah Teknik Industri
Published
2024-10-17
DOI
https://doi.org/10.37090/indstrk.v8i4.1616
Primary Topic
Management and Optimization Techniques
Type
article
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article

Peramalan Permintaan Minyak Goreng untuk Perencanaan Kebutuhan Crude Palm Oil di PT. PQS

Rahmi Elviana, Lisa Nesti, Meysha Azhara
Industrika Jurnal Ilmiah Teknik Industri
Management and Optimization Techniques
article

Peramalan Permintaan Minyak Goreng untuk Perencanaan Kebutuhan Crude Palm Oil di PT. PQS

Rahmi Elviana, Lisa Nesti, Meysha Azhara
article en

Abstract

PQS is a company engaged in the processing of Crude Palm Oil (CPO). The production system employed is make-to-stock, with production planning based on estimates and without the implementation of any specific method for production forecasting. Consequently, this has led to unmet consumer demand, with consumers having to wait until the cooking oil is available and distributed (out of stock). The objective of this research is to forecast the demand for cooking oil to plan for CPO needs and to determine the forecasted results for five periods, spanning from August to December 2023. The methods employed include Single Moving Average and Single Exponential Smoothing, validated by the POM-QM application. Based on the calculation results using the Single Moving Average method, an MAPE (Mean Absolute Percentage Error) of 13.12% was obtained, while the Single Exponential Smoothing method resulted in an MAPE of 14.44%. The chosen method for obtaining the most accurate forecasting method for cooking oil demand for CPO needs is the Single Moving Average method, as it has a smaller error rate. Keywords: Forecasting, Single Moving Average, Single Exponential Smoothing

Industrika Jurnal Ilmiah Teknik IndustriVol. 8(4)
Institut Teknologi Padang (ID)
Openalex Percentile: Top 61%
Management and Optimization Techniques
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