Analisis Fuzzy Time Series pada Jumlah Penumpang Kereta Api Whoosh dengan Markov Chain dan Lee
DOI:
https://doi.org/10.30605/proximal.v9i1.8009Keywords:
Fuzzy Time Series, Fuzzy Time Series Markov Chain, Metode Lee, Peramalan, Penumpang Kereta ApiAbstract
Fluktuasi jumlah penumpang Kereta Cepat Whoosh yang bersifat dinamis dan tidak linier menuntut adanya model peramalan yang akurat guna mendukung efisiensi operasional. Penelitian ini bertujuan untuk memprediksi jumlah penumpang Kereta Api Whoosh menggunakan kombinasi Fuzzy Time Series. Penelitian ini menggunakan pendekatan kuantitatif berbasis analisis deret waktu (time series) dengan penerapan metode Fuzzy Time Series yang dikombinasikan dengan Markov Chain dan metode Lee. Data yang digunakan adalah jumlah penumpang kereta api whoosh dari periode bulan April 2024–April 2025 yang diperoleh dari BPS. Kedua metode ini memiliki kemampuan yang baik dalam meramalkan data. Selanjutnya, keakuratan kedua metode dibandingkan melalui nilai evaluasi peramalan dengan menghitung MAE, MSE, RMSE, dan MAPE. Hasil Penelitian dari kedua metode tersebut diperoleh bahwa Fuzy Time Series Markov Chain lebih baik di bandingkan dengan Fuzzy Time series Markov Lee dengan nilai MAPE sebesar 9.04%, nilai MAE sebesar 42.553, nilai MSE sebesar 3216.050, dan RMSE sebesar 56.709. Sedangkan fuzzy time series lee mendapatkan nilai MAPE sebesar 9.07%, nilai MAE sebesar 42.529, nilai MSE sebesar 4466.798, dan RMSE sebesar 66.834. Hal ini menunjukkan bahwa fuzzy time series marcov chain lebih baik untuk peramalan jumlah penumpang kereta api whoosh karena menghasilkan nilai error yang lebih kecil.
References
Amiludin, S., & Mahbubah, N. A. (2023). Evaluasi Peramalan Permintaan Produk Kopi Bubuk Menggunakan Pendekatan Time Series Di Ukm Eyang Kakung - Gresik. Sigma Teknika, 6(1), 033–043. https://doi.org/10.33373/sigmateknika.v6i1.5289
Mendila, S. A., Utami, I. T., & Kartikasari, P. (2023). Peramalan Jumlah Penumpang Kereta Api Di Pulau Jawa Menggunakan Metode Holt Winters Exponential Smoothing Dan Fuzzy Time Series Markov Chain. Jurnal Gaussian, 12(1), 104–115. https://doi.org/10.14710/j.gauss.12.1.104-115
Nurlela, S., Fanani, A., & Hani Khaulasari. (2023). Harga Minyak Mentah WTI Menggunakan Metode Fuzzy Time Series Markov Chain. Jurnal Fourier, 12(1), 10–19. https://doi.org/10.14421/fourier.2023.121.10-19
Perdani, L. S., & Sriningsih, R. (2023). Penerapan Metode Fuzzy Time Series Model Chen dan Model Singh dalam Meramalkan Harga Cabai Merah Keriting di Provinsi Sumatra Barat. Jurnal Pendidikan Tambusai, Volume 8 N, 29275–29285. https://jptam.org/index.php/jptam/article/view/18775
Sugiono, K., & Herlina, M. (2024). Analisis Fuzzy Time Series pada Jumlah Penumpang Kereta Api di. Bandung Conference Series: Statistics, 4, 291–301.
Sumartini, Nor Hayati, M., & Wahyuningsih, S. (2017). Peramalan Menggunakan Metode Fuzzy Time Series Cheng Forecasting Using Fuzzy Time Series Cheng Method. Jurnal EKSPONENSIAL, 8(1). https://jurnal.fmipa.unmul.ac.id/index.php/exponensial/article/view/75
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