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PERBANDINGAN METODE DOUBLE EXPONENTIAL SMOOTHING HOLT DAN FUZZY TIME SERIES CHENG PADA PERAMALAN HARGA EMAS DI INDONESIA DILENGKAPI GUI R

*Fida Fauziyyah  -  Departemen Statistika, Fakultas Sains dan Matematika, Undip, Indonesia
Sugito Sugito  -  Department of Statistics, Faculty Science and Mathematics, Universitas Diponegoro, Indonesia
Rukun Santoso  -  Department of Statistics, Faculty Science and Mathematics, Universitas Diponegoro, Indonesia
Open Access Copyright 2024 Jurnal Gaussian under http://creativecommons.org/licenses/by-nc-sa/4.0.

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Abstract

Investment is placing a certain amount of money at this time to get some profit in the future. Investments are divided into three based on the period, namely short-term investments, medium-term investments, and long-term investments. Gold is an example of a good long-term investment. Gold price forecasting is an important thing to know when investing in gold. In this study, gold price data is divided into two parts, namely training data consisting of 674 data from 1 September 2020 to 6 July 2022 and testing data consisting of 75 data from 7 July 2022 to 19 September 2022. The data indicates that there is a trend element so it is suitable for analysis using the Double Exponential Smoothing Holt and Fuzzy Time Series Cheng. Data processing using the Double Exponential Smoothing Holt and Fuzzy Time Series Cheng methods is complemented by the creation of a Graphical User Interface (GUI) which can facilitate the process of selecting the best method. The analysis's findings indicate that Double Exponential Smoothing Holt (0.5427603%), which has a reduced MAPE value than Fuzzy Time Series Cheng (0.6053103%), is the best method.

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Keywords: Gold; Forecasting; Double Exponential Smoothing Holt; Fuzzy Time Series Cheng; GUI

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