Peramalan Harga Beras dengan Metode Double Exponential Smoothing dan Fuzzy Time Series (Study Kasus : Harga Beras di Kota Mataram)

Abstract

Rice has become the main staple food for almost the entire population of Indonesia. However, in Indonesia, the price of food commodities (rice) often fluctuates in price. Due to the rapid fluctuation of rice prices and the uncertainty in the future, it is necessary to forecast rice prices. This study aims to predict the price of rice in the city of Mataram using the Holt double exponential smoothing method and the Cheng fuzzy time series. The model's performance is based on Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE) indicators. Forecasting model based on Holt's double exponential smoothing method, the MSE value is 705967.4994 and the MAPE value is 7.91%. On the other hand, based on Cheng's fuzzy time series method, the performance of the forecasting model based on the MSE indicator is 566312.340 and based on the MAPE value of 6.75%. Based on these results, Cheng's fuzzy time series method is more accurate than Holt's double exponential smoothing method. Keywords: Double Exponential Smoothing Holt, Fuzzy Time Series Cheng, Rice Price, MAPE, MSE

Prediksi Harga Beras Belida Di Kota Pekanbaru Menggunakan Fuzzy Time Series Cheng

“…Seiring pertumbuhan penduduk yang cukup pesat, jumlah keperluan bahan pangan secara nasional cenderung mengalami peningkatan dari tahun ke tahun. Namun di Indonesia harga komoditas bahan pangan (misalnya beras dan lain-lain) sering mengalami fluktuasi harga [2]. Secara umum, harga beras mengalami kenaikan ataupun penurunan harga setiap bulan.…”

“…Untuk mengantisipasi kenaikan harga beras pemerintah perlu mengambil langkah preventif untuk mengurangi kenaikan harga beras [7]. Adanya fluktuasi harga beras yang begitu cepat dan tidak adanya kepastian di masa yang akan datang menuntut perlunya dilakukan peramalan harga beras [2].…”

Prediksi Jumlah Pendapatan Daerah Pada Kantor BPKPAD Dengan Metode Fuzzy Time Series

“…Defenisi 4: Jika F(t) disebabkan oleh F(t-1), F(t-2),...,F(t-n), fuzzy relationship diwakili oleh F(t-1), F(t-2),...,F(tn)→F(t) disebut dengan model orde ke n fuzzy time series. Apabila hasil fuzzyfikasi periode ke-i adalah dan tidak memiliki FLR pada FLRG dengan kondisi → ø, dimana nilai maksimum derajat keanggotaannya berada pada , maka nilai peramalan ( ) adalah nilai tengah dari atau didefenisikan dengan (Sulpaiyah et al, 2022); (Agustina, 2021).…”

Structural Time Series Model using Hamiltonian Monte Carlo for Rice Price

“…This study aims to find the best forecasting model for the average rice price at the Indonesian wholesale or wholesale trade level for July 2020 to June 2021 using the SARIMA (Seasonal Autoregressive Integrated Moving Average. Other forecasting techniques have also been applied, such as Holt's double exponential smoothing and Cheng's fuzzy time series method (Sulpaiyah et al, 2022). The application of the backpropagation method for rice price prediction also works well (Nafi'iyah & Khudori, 2022;Natasya et al, 2021).…”