Penerapan Fuzzy Time Series Markov Chain dalam Peramalan Harga Cabai Merah Berbasis Data Harian di Kabupaten Banyumas

Dian Kartika Sari, Iqsyahiro Kresna A, Diah Septiani

Abstract


Relatively high fluctuations in red chili prices often create challenges in maintaining food commodity price stability in various regions, including Banyumas Regency. Price changes influenced by weather conditions, supply availability, and market demand make red chili prices difficult to predict accurately. Therefore, a forecasting method capable of modeling uncertain and fluctuating time series data is needed. This study aims to forecast red chili prices in Banyumas Regency using the Fuzzy Time Series Markov Chain (FTSMC) model. The study used 317 daily price data points collected from January 1, 2025, to March 10, 2026. The research stages included determining the universe of discourse, constructing intervals and fuzzy sets, fuzzification, forming Fuzzy Logical Relationships (FLR) and Fuzzy Logical Relationship Groups (FLRG), constructing the Markov transition probability matrix, and performing defuzzification to obtain prediction values. The contribution of this study lies in applying the FTSMC method to model regional red chili price fluctuations with volatile characteristics and evaluating its performance using Mean Absolute Percentage Error (MAPE). The results indicate that the Fuzzy Time Series Markov Chain method can effectively model the fluctuation patterns of red chili prices. Based on the evaluation results, the prediction model achieved a MAPE value of 3.19\%, indicating very high prediction accuracy. Therefore, the FTSMC method can be used as an effective alternative forecasting model for predicting red chili prices and supporting decision-making related to food commodity price control in Banyumas Regency.

Keywords


Fuzzy Time Series Markov Chain; Red Chili Price Prediction; Time Series Forecasting; Food Commodities; Mean Absolute Percentage Error

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References


M. A. Bianto, B. Al-Badi, M. S. Alamsyah, and R. N. Rohman, “Sistem prediksi harga komoditas cabai di wilayah Jawa Timur menggunakan simple moving average,” Jurnal Informatika dan Teknik Elektro Terapan (JITET), vol. 13, no. 3, p. 2261, Jul. 2025, doi:10.23960/jitet.v13i3.7345.

M. Lim and T. Handhayani, “Penerapan LSTM dan GRU untuk prediksi harga cabai merah di Kota Jawa Timur,” Jurnal Informatika dan Teknik Elektro Terapan (JITET), vol. 13, no. 2, 2025, doi:10.23960/jitet.v13i2.6467.

U. Lenisa, S. Sugianti, and I. P. Astuti, “Prediksi harga cabai menggunakan fuzzy time series model Chen,” Jurnal Rekayasa Teknologi dan Komputasi, vol. 1, no. 1, Jun. 2025, doi:10.24269/jrtekom.v1i1.6430.

E. Prasetyo, R. Ramadhan, and A. Safitri, “Prediksi risiko gagal panen cabai rawit merah menggunakan algoritma decision tree,” Data Sciences Indonesia (DSI), vol. 5, no. 2, Dec. 2025, doi:10.47709/dsi.v5i2.7466.

A. R. H. Dwika and D. Avianto, “Implementasi algoritma LSTM untuk prediksi harga cabai merah keriting di Yogyakarta,” Jurnal Indonesia: Manajemen Informatika dan Komunikasi (JIMIK), vol. 5, no. 1, pp. 635–648, Jan. 2024, doi:10.35870/jimik.v5i1.534.

H. A. Anamsyah, I. G. S. M. Diyasa, and A. N. Sihananto, “Perbandingan model XGBoost, LSTM, dan Neural Prophet untuk prediksi harga cabai rawit merah di Jawa Timur,” dalam Prosiding Seminar Nasional Informatika Bela Negara (SANTIKA), vol. 5, no. 2, pp. 31–39, Dec. 2025.

Nurhamidah, P. M. Mustofa, and F. S. Mulyani, “Perbandingan metode fuzzy time series Lee dan Markov chain dalam peramalan harga cabai rawit (studi kasus Kota Tasikmalaya),” Proximal: Jurnal Penelitian Matematika dan Pendidikan Matematika, vol. 9, no. 1, pp. 206–217, Mar. 2026, doi:10.30605/proximal.v9i1.7992.

D. K. Sari, “Perbandingan fuzzy time series Chen dan Cheng untuk peramalan harga beras di Kabupaten Banyumas,” Euler: Jurnal Ilmiah Matematika, Sains dan Teknologi, vol. 12, no. 2, pp. 170–174, Dec. 2024, doi:10.37905/euler.v12i2.28012.

A. S. Amanda, P. Gultom, S. Sutarman, and A. Asima, “Penerapan fuzzy time series Markov chain dalam meramalkan nilai tukar rupiah terhadap yuan, dolar Amerika, dan dolar Singapura,” Innovative: Journal of Social Science Research, vol. 4, no. 4, pp. 1981–1997, Jul. 2024, doi:10.31004/innovative.v4i4.12328.

L. Sari, A. Romadloni, R. Listyaningrum, F. Hazrina, and N. W. Rahadi, “Metode fuzzy time series Markov chain untuk peramalan curah hujan harian,” Infotekmesin, vol. 15, no. 1, pp. 142–147, Jan. 2024, doi:10.35970/infotekmesin.v15i1.2182.

A. Martina, F. N. Sa’adah, and A. F. Huda, “Perbandingan metode fuzzy time series Markov chain dan fuzzy time series Cheng untuk peramalan data inflasi,” Jurnal TEKTRIKA, vol. 9, no. 1, pp. 17–22, 2024, doi:10.25124/tektrika.v9i1.6914.

R. A. Faroh, S. Nabilah, N. A. Affandy, N. Nafi’iyah, and M. Said, “Analisis peramalan data kekeringan lahan pertanian di Kabupaten Lamongan menggunakan metode fuzzy time series Markov chain,” AKSIOMA: Jurnal Matematika dan Pendidikan Matematika, vol. 16, no. 2, Sep. 2025, doi:10.26877/bd1eqb34.

A. D. Putri, E. Pujiastuti, and S. Sunarmi, “Peramalan harga emas menggunakan fuzzy time series-Markov chain,” Imajiner: Jurnal Matematika dan Pendidikan Matematika, vol. 7, no. 4, Jul. 2025, doi:10.26877/imajiner.v7i4.23893.

M. I. Ibaad, M. Siringoringo, I. Purnamasari, D. Yuniarti, and S. Suyitno, “Penerapan metode fuzzy time series Markov chain untuk meramalkan nilai transaksi belanja menggunakan uang elektronik di Indonesia,” Jurnal Gaussian, vol. 14, no. 2, pp. 290–301, Sep. 2025, doi:10.14710/j.gauss.14.2.290-301.

S. Nurlela, A. Fanani, and H. Khaulasari, “Prediksi harga minyak mentah WTI menggunakan metode fuzzy time series Markov chain,” Jurnal Fourier, vol. 12, no. 1, pp. 10–19, Apr. 2023, doi:10.14421/fourier.2023.121.10-19.

D. K. Sari and A. Sa’adah, “Forecasting rice prices in traditional markets in Banyumas Regency using fuzzy time series Chen,” BAREKENG: Journal of Mathematics and Its Applications, vol. 19, no. 1, pp. 503–510, 2025, doi:10.30598/barekengvol19iss1pp0503-0510.




DOI: https://doi.org/10.37905/euler.v14i2.37987

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