Nanda Aiken El Islamy
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Weekly Tofu Stock Prediction with Mamdani Fuzzy Method Nanda Aiken El Islamy; Tri Hastono; Adhitya Chandra Wibowo
Jurnal Publikasi Ilmu Komputer dan Multimedia Vol 3 No 1 (2024): Jurnal Publikasi Ilmu Komputer dan Multimedia
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupikom.v3i1.2584

Abstract

This research aims to predict weekly tofu stock using the Mamdani Fuzzy Method. This method is used to overcome the uncertainty and complexity in estimating tofu stock, which is influenced by various factors such as inventory, ingredients, and ingredient prices. By applying fuzzy logic to describe the uncertainty in the data, this model can provide more accurate stock predictions. This research involves collecting weekly tofu stock data from a specific time period and developing a fuzzy inference system based on relevant input variables. Experimental results and model validation show that the Mamdani Fuzzy Method can be an effective approach to predict weekly tofu stocks with satisfactory accuracy. The practical implications of this research can assist the tofu industry in optimizing inventory management and responding more appropriately to fluctuations in market demand.