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All Journal METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi
Muhammad Ilham 'Aziiz Alfarobi
Universitas Duta Bangsa Surakarta
Computer Science & IT

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SISTEM PREDIKSI VOLUME PENUMPANG HARIAN KRL YOGYAKARTA-SOLO MENGGUNAKAN MODEL HYBRID SARIMAX-PROPHET Muhammad Ilham 'Aziiz Alfarobi; Nurmalitasari; Ratna Puspita Indah
METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Vol. 12 No. 2 (2026): Volume 12 Nomor 2 Tahun 2026
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/mtk.v12i2.5721

Abstract

The operation of the Yogyakarta-Solo Commuter Line (KRL) since 2021 has become the backbone of transportation in the Yogyakarta Special Region and Central Java. However, highly dynamic fluctuations in passenger volume pose challenges for operational optimization. This research aims to develop an accurate daily passenger volume prediction system with a 30 day forecasting horizon to mitigate overcrowding and fleet inefficiency. The methodology employed is CRISP-DM, proposing a layered hybrid architecture based on residual modeling. In this model, SARIMAX serves as the primary pattern modeler (Layer 1), while Facebook Prophet acts as a residual corrector (Layer 2), optimized with selective correction mechanisms and daily adaptive weights. The research data covers the period from January 2025 to January 2026, totaling 396 observations. The test results show that the hybrid model provides the best performance compared to single models, achieving a Mean Absolute Percentage Error (MAPE) of 9.66% and a Mean Absolute Error (MAE) of 2,739 passengers per day. Utilizing historical data from January 2025 to January 2026, the modeling results are integrated into an interactive Streamlit dashboard as a practical decision support tool for KAI Commuter's proactive operational planning
Co-Authors Nurmalitasari Nurmalitasari Ratna Puspita Indah