Analysis of Gold Price Forecasts Using Automatic Clustering Method and Fuzzy Logic Relationship

Authors

  • Ro'i Khatul Jannah Universitas Negeri Padang, Padang, Indonesia
  • Dina Agustina Universitas Negeri Padang, Padang, Indonesia

DOI:

https://doi.org/10.30812/varian.v8i2.4382

Keywords:

ACFLR, Forecasting, Fuzzy Time Series, Gold, MAPE

Abstract

Gold is often chosen as an investment due to its lucrative potential. To maximize profits and avoid losses, investors need to understand the volatile price movements of gold. This research aims to forecast the price of gold in the next period. In this research, the forecasting method used is Automatic Clustering and Fuzzy Logical Relationship (ACFLR). ACFLR is a method that uses the concept of fuzzy logic for modeling time series data. The forecasting process includes data sorting, cluster formation, interval determination, fuzzification, FLR and FLRG formation, and calculation of forecasting values. Based on this method, the result of the gold price forecast in Padang City for the next period, namely January 2024 using the ACFLR method is IDR 978,796.9. with a MAPE value of 0.9%, which means this method is very good. For further researchers, it is hoped that the Fuzzy Time Series method can use other forecasting models in order to obtain the most optimal method for forecasting gold prices.

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Published

2025-07-31

Issue

Vol. 8 No. 2 (2025)

Section

Articles

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Copyright (c) 2025 Ro'i Khatul Jannah, Dina Agustina

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
“Analysis of Gold Price Forecasts Using Automatic Clustering Method and Fuzzy Logic Relationship”, JV, vol. 8, no. 2, pp. 165–178, Jul. 2025, doi: 10.30812/varian.v8i2.4382.