Perbandingan Tingkat Akurasi Metode Average Based Fuzzy Time Series Markov Chain dan Algoritma Novel Fuzzy Time Series

Syavira Habib Al-adawiyah, Evawati Alisah, Abdul Aziz

Abstract


Fuzzy time series method can be applied in predicting the situation in food price development data such as rice. The position of rice as a staple food has resulted in this commodity being one of the indicators of economic growth. The importance of suppressing rice prices so that they are stable can be done by forecasting rice prices in Indonesia in the future. The research method used for forecasting is average based fuzzy time series Markov chain and novel algorithms fuzzy time series. Researchers will compare the two methods in the case of rice prices by looking at the level of accuracy that is better. The data used in this study is the average monthly rice price at the wholesale trade level from January 2015 to March 2021 in units of Rp/Kg as much as 75 data. The results of the comparison of the level of accuracy using the value of Mean Absolute Percentage Error (MAPE), obtained the forecast of the average price of rice at the Indonesian wholesale trade level for average based fuzzy time series Markov chain which is 0.36%, while the MAPE value for novel algorithm fuzzy time series is 0.19%. Based on the MAPE results, it can be concluded that the novel algorithm method fuzzy time series produces a better level of accuracy compared to the method average based fuzzy time series Markov chain.


Keywords


Novel Algorithm Fuzzy Time Series; Average Based Fuzzy Time Series Markov Chain; rice price; MAPE; accuracy comparison

Full Text:

PDF

References


Maricar, Muhammad Azman, "Analisa Perbandingan Nilai Akurasi Moving Average dan Exponential Smoothing untuk Sistem Peramalan Pendapatan pada Perusahaan XYZ," Jurnal Sistem dan Informatika (JSI), 13(2), 36-45, 2019.

Wei, W. W, "Time series analysis," In The Oxford Handbook of Quantitative Methods in Psychology: Vol. 2, 2006.

Muhammad, Mahadi; Sri Wahyuningsih; and Meiliyani Siringoringo, "Peramalan nilai tukar petani subsektor peternakan menggunakan fuzzy time series lee," Jambura Journal of Mathematics, 3(1), 1-15, 2021.

Song, Q., & Chissom, B. S,“ Fuzzy time series and its models“. Fuzzy sets and systems, 54(3), 269-277, 1993.

Nugroho, Kristiawan, "Model Analisis Prediksi Menggunakan Metode Fuzzy Time Series," Infokam, 12(1), 2016.

Ekananta, Yulian, Penerapan Metode Average-Based Fuzzy Time Series Untuk Prediksi Konsumsi Energi Listrik Indonesia, Diss, Universitas Brawijaya, 2017.

Tsaur, Ruey-Chyn, "A fuzzy time series-Markov chain model with an application to forecast the exchange rate between the Taiwan and US dollar," International journal of innovative computing, information and control, 8(7), 4931-4942, 2012.

Jatipaningrum, Maria Titah, "Peramalan Data Produk Domestik Bruto dengan Fuzzy Time Series Markov Chain," Jurnal Teknologi, 9(1), 31-38, 2016.

Noh, Junaidi, Wijono Wijono, and Erni Yudaningtiyas, "Model Average Based FTS Markov Chain untuk Peramalan Penggunaan Bandwidth Jaringan Komputer," Jurnal EECCIS, 9(1), 31-36, 2015.

Jasim, Haneen T; Abdul G, Jasim Salim; Kais I, Ibrahim, " A novel algorithm to forecast enrollment based on fuzzy time series," Applications and Applied Mathematics: An International Journal, 7(1), 385-397, 2012.

Rukhansah, Nurmalia; Much Aziz Muslim; Riza Arifudin, "Fuzzy Time Series Markov Chain Dalam Meramalkan Harga Saham," Seminar Nasional Ilmu Komputer (Snik 2015), Semarang, Vol, 10, pp, 309-321, 2015.

Yudaruddin, Rizky, "Forecasting untuk Kegiatan Ekonomi dan Bisnis," RV Pustaka Horizon, 2019.

Yasrizal, Yasrizal, "Pengaruh Pembangunan Sektor Pertanian Terhadap Distribusi Pendapatan di Indonesia," Jurnal Bisnis Tani, 3 (1), 56-64, 2017.

Badan Pusat Statistik, “Luas Panen dan Produksi Beras di Indonesia 2019: Hasil Kegiatan Pendataan Statistik Pertanian Tanaman Pangan Terintegrasi Dengan Metode Kerangka Sampel Area. Jakarta: Badan Pusat Statistik”, 2019.

Nelly, Sofia; Safrida Safrida; Zakiah Zakiah, "Analisis Faktor-faktor yang Mempengaruhi Fluktuasi Harga Beras di Provinsi Aceh," Jurnal Ilmiah Mahasiswa Pertanian, 3(1), 178-191, 2018.

Hermawan, Iwan dan Eka Budiyanti, "Integrasi Harga Beras Era Perdagangan Terbuka dan Dampaknya Terhadap Swasembada dan Kesejahteraan Pelaku Ekonomi Beras," Buletin Ilmiah Litbang Perdagangan, 14(1), 21-46, 2020.

Guney, Hilal, Mehmet Akif Bakir, dan Cagdas Hakan Aladag, " A novel stochastic seasonal fuzzy time series forecasting model," International Journal of Fuzzy Systems, 20(3), 729-740, 2018.

Maharni, Ellina, Pemilihan Fuzzy Time Series Markov Chain Berbasis Rata-Rata Dan Fuzzy Time Series Markov Chain Dengan Fungsi Keanggotaan Gauss Pada Data Tingkat Inflasi Indonesia, Diss, Universitas Brawijaya, 2019.

Lee, Woo-Joo, dkk, " A novel forecasting method based on F-transform and fuzzy time series," International Journal of Fuzzy Systems, 19(6), 1793-1802, 2017.




DOI: https://doi.org/10.18860/jrmm.v1i3.14332

Refbacks

  • There are currently no refbacks.