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All Journal Compiler KACANEGARA Jurnal Pengabdian pada Masyarakat GERVASI: Jurnal Pengabdian kepada Masyarakat Jurnal Paedagogy Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat Jurnal Dinamika Informatika (JDI) Vortex Elementary School: Jurnal Pendidikan dan Pembelajaran ke-SD-an Journal of Innovative and Creativity
Rianto Rianto
Progam Studi Informatika Universitas PGRI Yogyakarta
Religion Aerospace Engineering Humanities Computer Science & IT Earth & Planetary Sciences Education Energy Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Nursing Public Health Social Sciences Other

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Comparative Analysis of Statistical and Machine Learning Models for Air Passenger Demand Forecasting: Evidence from Domestic and International Passenger Segments Rianto Rianto; Sri Mulyani; Setia Wardani
Vortex Vol 7, No 2 (2026)
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/vortex.v7i2.4015

Abstract

Accurate forecasting of air passenger demand is critical for aviation sector planning, yet model selection remains contested when data exhibit structural discontinuities and segment-specific behavior. This study benchmarks four forecasting approaches—SARIMA, SARIMAX, Prophet, and XGBoost—on monthly domestic and international passenger traffic data from 2019 to 2024, using a 12-month hold-out test set and a 36-month projection horizon. Model performance was evaluated using MAE, RMSE, and MAPE, with stationarity confirmed via Augmented Dickey-Fuller tests.Results reveal stark segmentation in model suitability. For international passengers, SARIMA achieved the lowest test MAPE (8.66%), substantially outperforming XGBoost (14.23%) and Prophet (57.65%), attributable to the strong first-order autocorrelation structure of post-recovery international traffic. For domestic passengers, SARIMA and SARIMAX both exhibited explosive forecast divergence (MAPE exceeding 11,900%), rendering them operationally unusable; XGBoost (MAPE 14.87%) emerged as the most reliable alternative by capturing non-linear interactions among lag features, rolling statistics, and annual trend components.The central finding concerns the role of exogenous variables: SARIMAX produced metrics identical to SARIMA for international passengers and marginally worse for domestic passengers, yielding no incremental predictive gain in either segment. This challenges the assumption that exogenous augmentation inherently improves seasonal time series models—such benefits are conditional on the relevance, stability, and non-redundancy of external regressors relative to existing seasonal components. These findings offer empirical guidance for segment-specific model selection in aviation demand forecasting and caution against uncritical adoption of SARIMAX when core seasonal structure is already sufficient.
Peningkatan Ekonomi Lokal Melalui Optimalisasi Desain Kemasan dan Digital Marketing Rianto Rianto; Anis Febri Nilansari; Mira Setiana
Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat Vol. 6 No. 1 (2026): Januari 2026 - Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/altifani.v6i1.942

Abstract

Pengabdian masyarakat ini dilakukan di Kulon Progo mengingat pentingnya digitalisasi dalam meningkatkan daya saing produk UMKM, khususnya bagi anggota IRT yang masih terbatas akses terhadap teknologi pemasaran. Kegiatan bertujuan meningkatkan kemampuan pemasaran digital dan diversifikasi mutu produk melalui pelatihan media sosial, pengelolaan website, serta strategi promosi digital. Pelatihan juga mencakup desain kemasan produk dan peningkatan kualitas untuk daya saing pasar. Metode yang digunakan adalah pendekatan dengan penyuluhan langsung, simulasi praktik, dan pendampingan. Hasilnya, peserta menunjukkan peningkatan pemahaman teknologi digital dan keterampilan pemasaran.  Kegiatan ini membuktikan bahwa penguatan kapasitas melalui pengabdian dapat mendorong peningkatan kemampuan bahkan akan berdampak pada kesejahteraan anggota IRT dan memperkuat citra produk lokal, sehingga hasilnya akan mempunyai dampak sosial dan ekonomi yang berkelanjutan.
Co-Authors Anis Febri Nilansari Anisa Fitri Ashari Ari Kusuma Wardana Eko Perianto Esti Setiawati Faiz Noormiyanto Gugum Gumilang Nurcahya Harliyus Agustian Istyawan Priyahapsara Luqman Hidayat Mira Setiana Palupi Sri Wijayanti Prahenusa Wahyu Ciptadi Rahmawati, Fajar Khanif Setia Wardani Sri Mulyani Sri Mulyani Sri Mulyani Sukasih Sukasih Taufik Agung Pranowo