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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Wikrama Parahita : Jurnal Pengabdian Masyarakat IJECA (International Journal of Education and Curriculum Application) Jurnal Teknik Informatika (JUTIF) Journal of Soft Computing Exploration Djtechno: Jurnal Teknologi Informasi
Setiyawan, Ramadhana
Universitas Negeri Yogyakarta, Indonesia
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Social Sciences

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Journal : Jurnal Teknik Informatika (JUTIF)

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Deep Learning Rnn-Lstm Model For Forecasting Tourist Visits In Yogyakarta Using Bps Time-Series Data Munir, Agus Qomaruddin; Wardani, Ratna; Setiyawan, Ramadhana; Mustofa, Zaenal; Nurkhamid, Nurkhamid
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 6 (2025): JUTIF Volume 6, Number 6, Desember 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.6.5467

Abstract

Tourism is a crucial sector in Indonesia's economic growth, particularly in Yogyakarta, contributing significantly to revenue, job creation, and infrastructure development. However, the COVID-19 pandemic has significantly impacted the tourism industry, making tourist arrival forecasting crucial for effective government policy decision-making. This study aims to predict tourist arrivals in Yogyakarta using deep learning models, specifically the Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) algorithms, chosen for their ability to process time series data and address non-linearity issues. Tourist arrival data from the Yogyakarta Central Statistics Agency (BPS) was used to train and test the model. Model evaluation was conducted using the Root Mean Squared Error (RMSE) metric to measure prediction accuracy. The results show that this model can accurately predict tourist arrival patterns, which can support strategic decision-making regarding the procurement of tourism facilities in Yogyakarta. The impact of this research is to provide practical benefits for local governments and tourism industry players in planning tourism promotion and management strategies. With more accurate predictions, relevant parties can prepare necessary resources and optimize tourism services according to projected visitor numbers.
Co-Authors 'Alam, Ghasa Faraasyatul Agus Qomaruddin Munir Herjuna Artanto Kusuma, Hanif Aulia Lismi Animatul Chisbiyah Nurkhamid, Nurkhamid Rahman, Dzul Fadli Ratna Wardani Retno Indah Rokhmawati Satrio Hadi Wijoyo Tiasari, Wulidah Ning Zaenal Mustofa