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All Journal Southeast Asian Business Review
Wildanu Ubaidillah
Jember State Polhytecnic
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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Control of Instant Pepper Inventory Based on Demand Forecasting Using Artifical Neural Network Backpropagation: A Case Study Labuna Factory Wildanu Ubaidillah; Ahmad Haris Hasanuddin Slamet; Septine Brillyantina; Rahmat Dhandy
Southeast Asian Business Review Vol. 4 No. 2 (2026): Vol. 4 No. 2 (2026): Southeast Asian Business Review - Vol. 4 No. 2 (2026)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/sabr.v4i2.78280

Abstract

The Pepper is one of the spices that has a very high economic value both in the national and international markets. Pepper is a necessary additional seasoning for food that has good business prospects. One of the manufacturing companies that processes instant ground pepper was Labuna factory. The demand for ground pepper often experiences fluctuating increases and decreases. Fluctuations in consumer demand patterns make it difficult for companies to determine production planning. Problems in procuring raw materials are an obstacle to the production of instant ground pepper. The availability of pepper raw materials on the market is not always stable and tends to fluctuate due to the influence of pepper productivity at the farmer level. Accurate forecasting of instant ground pepper demand can help Labuna factory optimize production planning by projecting raw material requirements for future production periods. The purpose of this study is to develop a backpropagation neural network (ANN) model for predicting pepper raw material requirements and controlling raw material inventory using the economic ordering method.
Co-Authors Ahmad Haris Hasanuddin Slamet Rahmat Dhandy Septine Brillyantina